[Boost-commit] svn:boost r42418 - in trunk: boost/accumulators boost/accumulators/framework boost/accumulators/framework/accumulators boost/accumulators/framework/parameters boost/accumulators/numeric boost/accumulators/numeric/detail boost/accumulators/numeric/functional boost/accumulators/statistics boost/accumulators/statistics/parameters boost/accumulators/statistics/variates doc doc/src libs/accumulators libs/accumulators/doc libs/accumulators/example libs/accumulators/test status

From: eric_at_[hidden]
Date: 2008-01-02 15:55:31

Author: eric_niebler
Date: 2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
New Revision: 42418
URL: http://svn.boost.org/trac/boost/changeset/42418

Log:
add accumulators
Added:
   trunk/boost/accumulators/
   trunk/boost/accumulators/accumulators.hpp   (contents, props changed)
   trunk/boost/accumulators/accumulators_fwd.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/
   trunk/boost/accumulators/framework/accumulator_base.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/accumulator_concept.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/accumulator_set.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/accumulators/
   trunk/boost/accumulators/framework/accumulators/droppable_accumulator.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/accumulators/external_accumulator.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/accumulators/reference_accumulator.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/accumulators/value_accumulator.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/depends_on.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/external.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/extractor.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/features.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/parameters/
   trunk/boost/accumulators/framework/parameters/accumulator.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/parameters/sample.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/parameters/weight.hpp   (contents, props changed)
   trunk/boost/accumulators/framework/parameters/weights.hpp   (contents, props changed)
   trunk/boost/accumulators/numeric/
   trunk/boost/accumulators/numeric/detail/
   trunk/boost/accumulators/numeric/detail/function1.hpp   (contents, props changed)
   trunk/boost/accumulators/numeric/detail/function2.hpp   (contents, props changed)
   trunk/boost/accumulators/numeric/detail/function3.hpp   (contents, props changed)
   trunk/boost/accumulators/numeric/detail/function4.hpp   (contents, props changed)
   trunk/boost/accumulators/numeric/detail/function_n.hpp   (contents, props changed)
   trunk/boost/accumulators/numeric/detail/pod_singleton.hpp   (contents, props changed)
   trunk/boost/accumulators/numeric/functional/
   trunk/boost/accumulators/numeric/functional.hpp   (contents, props changed)
   trunk/boost/accumulators/numeric/functional/complex.hpp   (contents, props changed)
   trunk/boost/accumulators/numeric/functional/valarray.hpp   (contents, props changed)
   trunk/boost/accumulators/numeric/functional/vector.hpp   (contents, props changed)
   trunk/boost/accumulators/numeric/functional_fwd.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/
   trunk/boost/accumulators/statistics.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/count.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/covariance.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/density.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/error_of.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/error_of_mean.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/extended_p_square.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/extended_p_square_quantile.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/kurtosis.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/max.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/mean.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/median.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/min.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/moment.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/p_square_cumulative_distribution.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/p_square_quantile.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/parameters/
   trunk/boost/accumulators/statistics/parameters/quantile_probability.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/peaks_over_threshold.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/pot_quantile.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/pot_tail_mean.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/skewness.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/stats.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/sum.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/tail.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/tail_mean.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/tail_quantile.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/tail_variate.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/tail_variate_means.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/times2_iterator.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/variance.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/variates/
   trunk/boost/accumulators/statistics/variates/covariate.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_covariance.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_density.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_extended_p_square.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_kurtosis.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_mean.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_median.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_moment.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_p_square_cumulative_distribution.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_p_square_quantile.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_peaks_over_threshold.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_skewness.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_sum.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_tail_mean.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_tail_quantile.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_tail_variate_means.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/weighted_variance.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics/with_error.hpp   (contents, props changed)
   trunk/boost/accumulators/statistics_fwd.hpp   (contents, props changed)
   trunk/libs/accumulators/
   trunk/libs/accumulators/doc/
   trunk/libs/accumulators/doc/Jamfile.v2   (contents, props changed)
   trunk/libs/accumulators/doc/accumulators.qbk   (contents, props changed)
   trunk/libs/accumulators/example/
   trunk/libs/accumulators/example/Jamfile.v2   (contents, props changed)
   trunk/libs/accumulators/example/example.vcproj   (contents, props changed)
   trunk/libs/accumulators/example/main.cpp   (contents, props changed)
   trunk/libs/accumulators/index.html   (contents, props changed)
   trunk/libs/accumulators/test/
   trunk/libs/accumulators/test/Jamfile.v2   (contents, props changed)
   trunk/libs/accumulators/test/count.cpp   (contents, props changed)
   trunk/libs/accumulators/test/covariance.cpp   (contents, props changed)
   trunk/libs/accumulators/test/droppable.cpp   (contents, props changed)
   trunk/libs/accumulators/test/error_of.cpp   (contents, props changed)
   trunk/libs/accumulators/test/extended_p_square.cpp   (contents, props changed)
   trunk/libs/accumulators/test/extended_p_square_quantile.cpp   (contents, props changed)
   trunk/libs/accumulators/test/external_accumulator.cpp   (contents, props changed)
   trunk/libs/accumulators/test/external_weights.cpp   (contents, props changed)
   trunk/libs/accumulators/test/kurtosis.cpp   (contents, props changed)
   trunk/libs/accumulators/test/max.cpp   (contents, props changed)
   trunk/libs/accumulators/test/mean.cpp   (contents, props changed)
   trunk/libs/accumulators/test/median.cpp   (contents, props changed)
   trunk/libs/accumulators/test/min.cpp   (contents, props changed)
   trunk/libs/accumulators/test/moment.cpp   (contents, props changed)
   trunk/libs/accumulators/test/p_square_cumulative_distribution.cpp   (contents, props changed)
   trunk/libs/accumulators/test/p_square_quantile.cpp   (contents, props changed)
   trunk/libs/accumulators/test/p_square_quantile_extended.cpp   (contents, props changed)
   trunk/libs/accumulators/test/pot_quantile.cpp   (contents, props changed)
   trunk/libs/accumulators/test/reference.cpp   (contents, props changed)
   trunk/libs/accumulators/test/skewness.cpp   (contents, props changed)
   trunk/libs/accumulators/test/sum.cpp   (contents, props changed)
   trunk/libs/accumulators/test/tail.cpp   (contents, props changed)
   trunk/libs/accumulators/test/tail_mean.cpp   (contents, props changed)
   trunk/libs/accumulators/test/tail_quantile.cpp   (contents, props changed)
   trunk/libs/accumulators/test/tail_variate_means.cpp   (contents, props changed)
   trunk/libs/accumulators/test/valarray.cpp   (contents, props changed)
   trunk/libs/accumulators/test/value.cpp   (contents, props changed)
   trunk/libs/accumulators/test/variance.cpp   (contents, props changed)
   trunk/libs/accumulators/test/vector.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_covariance.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_extended_p_square.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_kurtosis.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_mean.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_median.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_moment.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_p_square_cum_dist.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_p_square_quantile.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_pot_quantile.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_skewness.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_sum.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_tail_mean.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_tail_quantile.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_tail_variate_means.cpp   (contents, props changed)
   trunk/libs/accumulators/test/weighted_variance.cpp   (contents, props changed)
Text files modified: 
   trunk/doc/Jamfile.v2    |     5 +++++                                   
   trunk/doc/src/boost.xml |     2 ++                                      
   trunk/status/Jamfile.v2 |     1 +                                       
   3 files changed, 8 insertions(+), 0 deletions(-)

Added: trunk/boost/accumulators/accumulators.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/accumulators.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,27 @@
+///////////////////////////////////////////////////////////////////////////////
+/// \file accumulators.hpp
+/// Includes all of the Accumulators Framework
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_ACCUMULATORS_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_ACCUMULATORS_HPP_EAN_28_10_2005
+
+#include <boost/accumulators/framework/accumulator_set.hpp>
+#include <boost/accumulators/framework/accumulator_concept.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/external.hpp>
+#include <boost/accumulators/framework/features.hpp>
+#include <boost/accumulators/framework/parameters/accumulator.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/parameters/weight.hpp>
+#include <boost/accumulators/framework/parameters/weights.hpp>
+#include <boost/accumulators/framework/accumulators/external_accumulator.hpp>
+#include <boost/accumulators/framework/accumulators/droppable_accumulator.hpp>
+#include <boost/accumulators/framework/accumulators/reference_accumulator.hpp>
+#include <boost/accumulators/framework/accumulators/value_accumulator.hpp>
+
+#endif

Added: trunk/boost/accumulators/accumulators_fwd.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/accumulators_fwd.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,211 @@
+///////////////////////////////////////////////////////////////////////////////
+// accumulators_fwd.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_ACCUMULATORS_FWD_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_ACCUMULATORS_FWD_HPP_EAN_28_10_2005
+
+#include <boost/config.hpp>
+#include <boost/mpl/apply_fwd.hpp> // for mpl::na
+#include <boost/mpl/limits/vector.hpp>
+#include <boost/preprocessor/arithmetic/inc.hpp>
+#include <boost/preprocessor/repetition/enum_params_with_a_default.hpp>
+#include <boost/preprocessor/repetition/enum_trailing_params.hpp>
+#include <boost/preprocessor/repetition/enum_trailing_binary_params.hpp>
+#include <boost/preprocessor/repetition/repeat_from_to.hpp>
+#include <boost/accumulators/numeric/functional_fwd.hpp>
+
+#ifndef BOOST_ACCUMULATORS_MAX_FEATURES
+  /// The maximum number of accumulators that may be put in an accumulator_set.
+  /// Defaults to BOOST_MPL_LIMIT_VECTOR_SIZE (which defaults to 20).
+# define BOOST_ACCUMULATORS_MAX_FEATURES BOOST_MPL_LIMIT_VECTOR_SIZE
+#endif
+
+#if BOOST_ACCUMULATORS_MAX_FEATURES > BOOST_MPL_LIMIT_VECTOR_SIZE
+# error BOOST_ACCUMULATORS_MAX_FEATURES cannot be larger than BOOST_MPL_LIMIT_VECTOR_SIZE
+#endif
+
+#ifndef BOOST_ACCUMULATORS_MAX_ARGS
+  /// The maximum number of arguments that may be specified to an accumulator_set's
+  /// accumulation function. Defaults to 15.
+# define BOOST_ACCUMULATORS_MAX_ARGS 15
+#endif
+
+#if BOOST_WORKAROUND(__GNUC__, == 3) \
+ || BOOST_WORKAROUND(__EDG_VERSION__, BOOST_TESTED_AT(306))
+# define BOOST_ACCUMULATORS_BROKEN_CONST_OVERLOADS
+#endif
+
+#ifdef BOOST_ACCUMULATORS_BROKEN_CONST_OVERLOADS
+# include <boost/utility/enable_if.hpp>
+# include <boost/type_traits/is_const.hpp>
+# define BOOST_ACCUMULATORS_PROTO_DISABLE_IF_IS_CONST(T)\
+    , typename boost::disable_if<boost::is_const<T> >::type * = 0
+#else
+# define BOOST_ACCUMULATORS_PROTO_DISABLE_IF_IS_CONST(T)
+#endif
+
+namespace boost { namespace accumulators
+{
+
+///////////////////////////////////////////////////////////////////////////////
+// Named parameters tags
+//
+namespace tag
+{
+    struct sample;
+    struct weight;
+    struct accumulator;
+    struct weights;
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// User-level features
+//
+namespace tag
+{
+    template<typename ValueType, typename Tag>
+    struct value;
+
+    template<typename Tag>
+    struct value_tag;
+
+    template<typename Referent, typename Tag>
+    struct reference;
+
+    template<typename Tag>
+    struct reference_tag;
+
+    template<typename Type, typename Tag = void, typename AccumulatorSet = void>
+    struct external;
+
+    template<typename Feature>
+    struct droppable;
+}
+
+template<typename Accumulator>
+struct droppable_accumulator_base;
+
+template<typename Accumulator>
+struct droppable_accumulator;
+
+template<typename Accumulator>
+struct with_cached_result;
+
+template<typename Sample, typename Features, typename Weight = void>
+struct accumulator_set;
+
+template<typename Feature>
+struct extractor;
+
+template<typename Feature>
+struct feature_of;
+
+template<typename Feature>
+struct as_feature;
+
+template<typename Feature>
+struct as_weighted_feature;
+
+template<BOOST_PP_ENUM_PARAMS_WITH_A_DEFAULT(BOOST_ACCUMULATORS_MAX_FEATURES, typename Feature, mpl::na)>
+struct depends_on;
+
+template<BOOST_PP_ENUM_PARAMS_WITH_A_DEFAULT(BOOST_ACCUMULATORS_MAX_FEATURES, typename Feature, mpl::na)>
+struct features;
+
+template<typename Feature, typename AccumulatorSet>
+typename mpl::apply<AccumulatorSet, Feature>::type const &
+find_accumulator(AccumulatorSet const &acc);
+
+template<typename Feature, typename AccumulatorSet>
+typename mpl::apply<AccumulatorSet, Feature>::type::result_type
+extract_result(AccumulatorSet const &acc);
+
+template<typename Feature, typename AccumulatorSet, typename A1>
+typename mpl::apply<AccumulatorSet, Feature>::type::result_type
+extract_result(AccumulatorSet const &acc, A1 const &a1);
+
+// ... other overloads generated by Boost.Preprocessor:
+
+/// INTERNAL ONLY
+///
+#define BOOST_ACCUMULATORS_EXTRACT_RESULT_FWD(z, n, _)                      \
+    template<                                                               \
+        typename Feature                                                    \
+      , typename AccumulatorSet                                             \
+        BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, typename A)                   \
+    >                                                                       \
+    typename mpl::apply<AccumulatorSet, Feature>::type::result_type         \
+    extract_result(                                                         \
+        AccumulatorSet const &acc                                           \
+        BOOST_PP_ENUM_TRAILING_BINARY_PARAMS_Z(z, n, A, const &a)           \
+    );
+
+/// INTERNAL ONLY
+///
+BOOST_PP_REPEAT_FROM_TO(
+    2
+  , BOOST_PP_INC(BOOST_ACCUMULATORS_MAX_ARGS)
+  , BOOST_ACCUMULATORS_EXTRACT_RESULT_FWD
+  , _
+)
+
+#ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED
+template<typename Feature, typename AccumulatorSet, typename A1, typename A2 ...>
+typename mpl::apply<AccumulatorSet, Feature>::type::result_type
+extract_result(AccumulatorSet const &acc, A1 const &a1, A2 const &a2 ...);
+#endif
+
+namespace impl
+{
+    using namespace numeric::operators;
+
+    template<typename Accumulator, typename Tag>
+    struct external_impl;
+}
+
+namespace detail
+{
+    template<typename Accumulator>
+    struct feature_tag;
+
+    template<typename Feature, typename Sample, typename Weight>
+    struct to_accumulator;
+
+    struct accumulator_set_base;
+
+    template<typename T>
+    struct is_accumulator_set;
+}
+
+}} // namespace boost::accumulators
+
+// For defining boost::parameter keywords that can be inherited from to
+// get a nested, class-scoped keyword with the requested alias
+#define BOOST_PARAMETER_NESTED_KEYWORD(tag_namespace, name, alias)                                  \
+    namespace tag_namespace                                                                         \
+    {                                                                                               \
+        template<int Dummy = 0>                                                                     \
+        struct name ## _                                                                            \
+        {                                                                                           \
+            static char const* keyword_name()                                                       \
+            {                                                                                       \
+                return #name;                                                                       \
+            }                                                                                       \
+            static ::boost::parameter::keyword<name ## _<Dummy> > &alias;                           \
+        };                                                                                          \
+        template<int Dummy>                                                                         \
+        ::boost::parameter::keyword<name ## _<Dummy> > &name ## _<Dummy>::alias =                   \
+        ::boost::parameter::keyword<name ## _<Dummy> >::get();                                      \
+        typedef name ## _ <> name;                                                                  \
+    }                                                                                               \
+    namespace                                                                                       \
+    {                                                                                               \
+        ::boost::parameter::keyword<tag_namespace::name> &name =                                    \
+        ::boost::parameter::keyword<tag_namespace::name>::get();                                    \
+    }
+
+#endif

Added: trunk/boost/accumulators/framework/accumulator_base.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/accumulator_base.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,65 @@
+///////////////////////////////////////////////////////////////////////////////
+// accumulator_base.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_BASE_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_BASE_HPP_EAN_28_10_2005
+
+#include <boost/mpl/placeholders.hpp>
+#include <boost/mpl/joint_view.hpp>
+#include <boost/mpl/single_view.hpp>
+#include <boost/mpl/fold.hpp>
+#include <boost/mpl/contains.hpp>
+#include <boost/mpl/empty_sequence.hpp>
+#include <boost/accumulators/framework/accumulator_concept.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace detail
+{
+    typedef void void_;
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// dont_care
+//
+struct dont_care
+{
+    template<typename Args>
+    dont_care(Args const &)
+    {
+    }
+};
+
+///////////////////////////////////////////////////////////////////////////////
+// accumulator_base
+//
+struct accumulator_base
+{
+    // hidden if defined in derived classes
+    detail::void_ operator ()(dont_care)
+    {
+    }
+
+    typedef mpl::false_ is_droppable;
+
+    detail::void_ add_ref(dont_care)
+    {
+    }
+
+    detail::void_ drop(dont_care)
+    {
+    }
+
+    detail::void_ on_drop(dont_care)
+    {
+    }
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/accumulator_concept.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/accumulator_concept.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,29 @@
+///////////////////////////////////////////////////////////////////////////////
+// accumulator_concept.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATOR_CONCEPT_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATOR_CONCEPT_HPP_EAN_28_10_2005
+
+#include <boost/concept_check.hpp>
+
+namespace boost { namespace accumulators
+{
+
+template<typename Stat>
+struct accumulator_concept
+{
+    void constraints()
+    {
+        // TODO: define the stat concept
+    }
+
+    Stat stat;
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/accumulator_set.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/accumulator_set.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,396 @@
+///////////////////////////////////////////////////////////////////////////////
+// accumulator_set.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATOR_SET_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATOR_SET_HPP_EAN_28_10_2005
+
+#include <boost/version.hpp>
+#include <boost/mpl/apply.hpp>
+#include <boost/mpl/assert.hpp>
+#include <boost/mpl/protect.hpp>
+#include <boost/mpl/identity.hpp>
+#include <boost/mpl/is_sequence.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/type_traits/is_base_and_derived.hpp>
+#include <boost/parameter/parameters.hpp>
+#include <boost/preprocessor/repetition/repeat_from_to.hpp>
+#include <boost/preprocessor/repetition/enum_binary_params.hpp>
+#include <boost/accumulators/accumulators_fwd.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/framework/accumulator_concept.hpp>
+#include <boost/accumulators/framework/parameters/accumulator.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/accumulators/external_accumulator.hpp>
+#include <boost/accumulators/framework/accumulators/droppable_accumulator.hpp>
+#include <boost/fusion/include/any.hpp>
+#include <boost/fusion/include/find_if.hpp>
+#include <boost/fusion/include/for_each.hpp>
+#include <boost/fusion/include/filter_view.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace detail
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // accumulator_visitor
+    //   wrap a boost::parameter argument pack in a Fusion extractor object
+    template<typename Args>
+    struct accumulator_visitor
+    {
+        explicit accumulator_visitor(Args const &args)
+          : args(args)
+        {
+        }
+
+        template<typename Accumulator>
+        void operator ()(Accumulator &accumulator) const
+        {
+            accumulator(this->args);
+        }
+
+    private:
+        Args const &args;
+    };
+
+    template<typename Args>
+    inline accumulator_visitor<Args> const make_accumulator_visitor(Args const &args)
+    {
+        return accumulator_visitor<Args>(args);
+    }
+
+    typedef
+        parameter::parameters<
+            parameter::required<tag::accumulator>
+          , parameter::optional<tag::sample>
+          // ... and others which are not specified here...
+        >
+    accumulator_params;
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // accumulator_set_base
+    struct accumulator_set_base
+    {
+    };
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // is_accumulator_set
+    template<typename T>
+    struct is_accumulator_set
+      : is_base_and_derived<accumulator_set_base, T>
+    {
+    };
+
+} // namespace detail
+
+#ifdef _MSC_VER
+#pragma warning(push)
+#pragma warning(disable: 4355) // warning C4355: 'this' : used in base member initializer list
+#endif
+
+///////////////////////////////////////////////////////////////////////////////
+/// \brief A set of accumulators.
+///
+/// accumulator_set resolves the dependencies between features and ensures that
+/// the accumulators in the set are updated in the proper order.
+///
+/// acccumulator_set provides a general mechanism to visit the accumulators
+/// in the set in order, with or without a filter. You can also fetch a reference
+/// to an accumulator that corresponds to a feature.
+///
+template<typename Sample, typename Features, typename Weight>
+struct accumulator_set
+  : detail::accumulator_set_base
+{
+    typedef Sample sample_type;     ///< The type of the samples that will be accumulated
+    typedef Features features_type; ///< An MPL sequence of the features that should be accumulated.
+    typedef Weight weight_type;     ///< The type of the weight parameter. Must be a scalar. Defaults to void.
+
+    /// INTERNAL ONLY
+    ///
+    typedef
+        typename detail::make_accumulator_tuple<
+            Features
+          , Sample
+          , Weight
+        >::type
+    accumulators_mpl_vector;
+
+    // generate a fusion::list of accumulators
+    /// INTERNAL ONLY
+    ///
+    typedef
+        typename detail::meta::make_acc_list<
+            accumulators_mpl_vector
+        >::type
+    accumulators_type;
+
+    /// INTERNAL ONLY
+    ///
+    //BOOST_MPL_ASSERT((mpl::is_sequence<accumulators_type>));
+
+    ///////////////////////////////////////////////////////////////////////////////
+    /// default-construct all contained accumulators
+    accumulator_set()
+      : accumulators(
+            detail::make_acc_list(
+                accumulators_mpl_vector()
+              , detail::accumulator_params()(*this)
+            )
+        )
+    {
+        // Add-ref the Features that the user has specified
+        this->template visit_if<detail::contains_feature_of_<Features> >(
+            detail::make_add_ref_visitor(detail::accumulator_params()(*this))
+        );
+    }
+
+    /// \overload
+    ///
+    /// \param a1 Optional named parameter to be passed to all the accumulators
+    template<typename A1>
+    explicit accumulator_set(A1 const &a1)
+      : accumulators(
+            detail::make_acc_list(
+                accumulators_mpl_vector()
+              , detail::accumulator_params()(*this, a1)
+            )
+        )
+    {
+        // Add-ref the Features that the user has specified
+        this->template visit_if<detail::contains_feature_of_<Features> >(
+            detail::make_add_ref_visitor(detail::accumulator_params()(*this))
+        );
+    }
+
+    // ... other overloads generated by Boost.Preprocessor:
+
+    /// INTERNAL ONLY
+    ///
+#define BOOST_ACCUMULATORS_ACCUMULATOR_SET_CTOR(z, n, _)                                \
+    template<BOOST_PP_ENUM_PARAMS_Z(z, n, typename A)>                                  \
+    accumulator_set(BOOST_PP_ENUM_BINARY_PARAMS_Z(z, n, A, const &a))                   \
+      : accumulators(                                                                   \
+            detail::make_acc_list(                                                      \
+                accumulators_mpl_vector()                                               \
+              , detail::accumulator_params()(                                           \
+                    *this BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, a)                      \
+                )                                                                       \
+            )                                                                           \
+        )                                                                               \
+    {                                                                                   \
+        /* Add-ref the Features that the user has specified */                          \
+        this->template visit_if<detail::contains_feature_of_<Features> >(               \
+            detail::make_add_ref_visitor(detail::accumulator_params()(*this))           \
+        );                                                                              \
+    }
+
+    /// INTERNAL ONLY
+    ///
+    BOOST_PP_REPEAT_FROM_TO(
+        2
+      , BOOST_PP_INC(BOOST_ACCUMULATORS_MAX_ARGS)
+      , BOOST_ACCUMULATORS_ACCUMULATOR_SET_CTOR
+      , _
+    )
+
+    #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED
+    /// \overload
+    ///
+    template<typename A1, typename A2, ...>
+    accumulator_set(A1 const &a1, A2 const &a2, ...);
+    #endif
+
+    // ... other overloads generated by Boost.Preprocessor below ...
+
+    ///////////////////////////////////////////////////////////////////////////////
+    /// Visitation
+    /// \param func UnaryFunction which is invoked with each accumulator in turn.
+    template<typename UnaryFunction>
+    void visit(UnaryFunction const &func)
+    {
+        fusion::for_each(this->accumulators, func);
+    }
+
+    ///////////////////////////////////////////////////////////////////////////////
+    /// Conditional visitation
+    /// \param func UnaryFunction which is invoked with each accumulator in turn,
+    ///     provided the accumulator satisfies the MPL predicate FilterPred.
+    template<typename FilterPred, typename UnaryFunction>
+    void visit_if(UnaryFunction const &func)
+    {
+        fusion::filter_view<accumulators_type, FilterPred> filtered_accs(this->accumulators);
+        fusion::for_each(filtered_accs, func);
+    }
+
+    ///////////////////////////////////////////////////////////////////////////////
+    /// Accumulation
+    /// \param a1 Optional named parameter to be passed to all the accumulators
+    void operator ()()
+    {
+        this->visit(
+            detail::make_accumulator_visitor(
+                detail::accumulator_params()(*this)
+            )
+        );
+    }
+
+    template<typename A1>
+    void operator ()(A1 const &a1)
+    {
+        this->visit(
+            detail::make_accumulator_visitor(
+                detail::accumulator_params()(*this, a1)
+            )
+        );
+    }
+
+    // ... other overloads generated by Boost.Preprocessor:
+
+    /// INTERNAL ONLY
+    ///
+#define BOOST_ACCUMULATORS_ACCUMULATOR_SET_FUN_OP(z, n, _)                              \
+    template<BOOST_PP_ENUM_PARAMS_Z(z, n, typename A)>                                  \
+    void operator ()(BOOST_PP_ENUM_BINARY_PARAMS_Z(z, n, A, const &a))                  \
+    {                                                                                   \
+        this->visit(                                                                    \
+            detail::make_accumulator_visitor(                                           \
+                detail::accumulator_params()(                                           \
+                    *this BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, a)                      \
+                )                                                                       \
+            )                                                                           \
+        );                                                                              \
+    }
+
+    /// INTERNAL ONLY
+    ///
+    BOOST_PP_REPEAT_FROM_TO(
+        2
+      , BOOST_PP_INC(BOOST_ACCUMULATORS_MAX_ARGS)
+      , BOOST_ACCUMULATORS_ACCUMULATOR_SET_FUN_OP
+      , _
+    )
+
+    #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED
+    /// \overload
+    ///
+    template<typename A1, typename A2, ...>
+    void operator ()(A1 const &a1, A2 const &a2, ...);
+    #endif
+
+    ///////////////////////////////////////////////////////////////////////////////
+    /// Extraction
+    template<typename Feature>
+    struct apply
+      : fusion::result_of::value_of<
+            typename fusion::result_of::find_if<
+                accumulators_type
+              , detail::matches_feature<Feature>
+            >::type
+        >
+    {
+    };
+
+    ///////////////////////////////////////////////////////////////////////////////
+    /// Extraction
+    template<typename Feature>
+    typename apply<Feature>::type &extract()
+    {
+        return *fusion::find_if<detail::matches_feature<Feature> >(this->accumulators);
+    }
+
+    /// \overload
+    template<typename Feature>
+    typename apply<Feature>::type const &extract() const
+    {
+        return *fusion::find_if<detail::matches_feature<Feature> >(this->accumulators);
+    }
+
+    ///////////////////////////////////////////////////////////////////////////////
+    /// Drop
+    template<typename Feature>
+    void drop()
+    {
+        // You can only drop the features that you have specified explicitly
+        typedef typename apply<Feature>::type the_accumulator;
+        BOOST_MPL_ASSERT((detail::contains_feature_of<Features, the_accumulator>)); 
+
+        typedef 
+            typename feature_of<typename as_feature<Feature>::type>::type
+        the_feature;
+
+        (*fusion::find_if<detail::matches_feature<Feature> >(this->accumulators))
+            .drop(detail::accumulator_params()(*this));
+
+        // Also drop accumulators that this feature depends on
+        typedef typename the_feature::dependencies dependencies;
+        this->template visit_if<detail::contains_feature_of_<dependencies> >(
+            detail::make_drop_visitor(detail::accumulator_params()(*this))
+        );
+    }
+
+private:
+
+    accumulators_type accumulators;
+};
+
+#ifdef _MSC_VER
+#pragma warning(pop)
+#endif
+
+///////////////////////////////////////////////////////////////////////////////
+// find_accumulator
+//   find an accumulator in an accumulator_set corresponding to a feature
+template<typename Feature, typename AccumulatorSet>
+typename mpl::apply<AccumulatorSet, Feature>::type &
+find_accumulator(AccumulatorSet &acc BOOST_ACCUMULATORS_PROTO_DISABLE_IF_IS_CONST(AccumulatorSet))
+{
+    return acc.template extract<Feature>();
+}
+
+/// \overload
+template<typename Feature, typename AccumulatorSet>
+typename mpl::apply<AccumulatorSet, Feature>::type const &
+find_accumulator(AccumulatorSet const &acc)
+{
+    return acc.template extract<Feature>();
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract_result
+//   extract a result from an accumulator set
+/// INTERNAL ONLY
+///
+#define BOOST_ACCUMULATORS_EXTRACT_RESULT_FUN(z, n, _)                      \
+    template<                                                               \
+        typename Feature                                                    \
+      , typename AccumulatorSet                                             \
+        BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, typename A)                   \
+    >                                                                       \
+    typename mpl::apply<AccumulatorSet, Feature>::type::result_type         \
+    extract_result(                                                         \
+        AccumulatorSet const &acc                                           \
+        BOOST_PP_ENUM_TRAILING_BINARY_PARAMS_Z(z, n, A, const &a)           \
+    )                                                                       \
+    {                                                                       \
+        return find_accumulator<Feature>(acc).result(                       \
+            detail::accumulator_params()(                                   \
+                acc                                                         \
+                BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, a)                    \
+            )                                                               \
+        );                                                                  \
+    }
+
+BOOST_PP_REPEAT(
+    BOOST_PP_INC(BOOST_ACCUMULATORS_MAX_ARGS)
+  , BOOST_ACCUMULATORS_EXTRACT_RESULT_FUN
+  , _
+)
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/accumulators/droppable_accumulator.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/accumulators/droppable_accumulator.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,313 @@
+///////////////////////////////////////////////////////////////////////////////
+// droppable_accumulator.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_DROPPABLE_ACCUMULATOR_HPP_EAN_13_12_2005
+#define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_DROPPABLE_ACCUMULATOR_HPP_EAN_13_12_2005
+
+#include <new>
+#include <boost/assert.hpp>
+#include <boost/mpl/apply.hpp>
+#include <boost/aligned_storage.hpp>
+#include <boost/accumulators/framework/depends_on.hpp> // for feature_of
+
+namespace boost { namespace accumulators
+{
+
+    template<typename Accumulator>
+    struct droppable_accumulator;
+
+    namespace detail
+    {
+        ///////////////////////////////////////////////////////////////////////////////
+        // add_ref_visitor
+        //   a fusion function object for add_ref'ing accumulators
+        template<typename Args>
+        struct add_ref_visitor
+        {
+            explicit add_ref_visitor(Args const &args)
+              : args_(args)
+            {
+            }
+
+            template<typename Accumulator>
+            void operator ()(Accumulator &acc) const
+            {
+                typedef typename Accumulator::feature_tag::dependencies dependencies;
+
+                acc.add_ref(this->args_);
+
+                // Also add_ref accumulators that this feature depends on
+                this->args_[accumulator].template 
+                    visit_if<detail::contains_feature_of_<dependencies> >(
+                        *this
+                );
+            }
+
+        private:
+            Args const &args_;
+        };
+
+        template<typename Args>
+        add_ref_visitor<Args> make_add_ref_visitor(Args const &args)
+        {
+            return add_ref_visitor<Args>(args);
+        }
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // drop_visitor
+        //   a fusion function object for dropping accumulators
+        template<typename Args>
+        struct drop_visitor
+        {
+            explicit drop_visitor(Args const &args)
+              : args_(args)
+            {
+            }
+
+            template<typename Accumulator>
+            void operator ()(Accumulator &acc) const
+            {
+                if(typename Accumulator::is_droppable())
+                {
+                    typedef typename Accumulator::feature_tag::dependencies dependencies;
+
+                    acc.drop(this->args_);
+                    // Also drop accumulators that this feature depends on
+                    this->args_[accumulator].template 
+                        visit_if<detail::contains_feature_of_<dependencies> >(
+                            *this
+                    );
+                }
+            }
+
+        private:
+            Args const &args_;
+        };
+
+        template<typename Args>
+        drop_visitor<Args> make_drop_visitor(Args const &args)
+        {
+            return drop_visitor<Args>(args);
+        }
+    }
+
+    //////////////////////////////////////////////////////////////////////////
+    // droppable_accumulator_base
+    template<typename Accumulator>
+    struct droppable_accumulator_base
+      : Accumulator
+    {
+        typedef mpl::true_ is_droppable;
+        typedef typename Accumulator::result_type result_type;
+
+        template<typename Args>
+        droppable_accumulator_base(Args const &args)
+          : Accumulator(args)
+          , ref_count_(0)
+        {
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            if(!this->is_dropped())
+            {
+                this->Accumulator::operator ()(args);
+            }
+        }
+
+        template<typename Args>
+        void add_ref(Args const &args)
+        {
+            ++this->ref_count_;
+        }
+
+        template<typename Args>
+        void drop(Args const &args)
+        {
+            BOOST_ASSERT(0 < this->ref_count_);
+            if(1 == this->ref_count_)
+            {
+                static_cast<droppable_accumulator<Accumulator> *>(this)->on_drop(args);
+            }
+            --this->ref_count_;
+        }
+
+        bool is_dropped() const
+        {
+            return 0 == this->ref_count_;
+        }
+
+    private:
+        int ref_count_;
+    };
+
+    //////////////////////////////////////////////////////////////////////////
+    // droppable_accumulator
+    //   this can be specialized for any type that needs special handling
+    template<typename Accumulator>
+    struct droppable_accumulator
+      : droppable_accumulator_base<Accumulator>
+    {
+        template<typename Args>
+        droppable_accumulator(Args const &args)
+          : droppable_accumulator_base<Accumulator>(args)
+        {
+        }
+    };
+
+    //////////////////////////////////////////////////////////////////////////
+    // with_cached_result
+    template<typename Accumulator>
+    struct with_cached_result
+      : Accumulator
+    {
+        typedef typename Accumulator::result_type result_type;
+
+        template<typename Args>
+        with_cached_result(Args const &args)
+          : Accumulator(args)
+          , cache()
+        {
+        }
+
+        with_cached_result(with_cached_result const &that)
+          : Accumulator(*static_cast<Accumulator const *>(&that))
+          , cache()
+        {
+            if(that.has_result())
+            {
+                this->set(that.get());
+            }
+        }
+
+        ~with_cached_result()
+        {
+            // Since this is a base class of droppable_accumulator_base,
+            // this destructor is called before any of droppable_accumulator_base's
+            // members get cleaned up, including is_dropped, so the following
+            // call to has_result() is valid.
+            if(this->has_result())
+            {
+                this->get().~result_type();
+            }
+        }
+
+        template<typename Args>
+        void on_drop(Args const &args)
+        {
+            // cache the result at the point this calcuation was dropped
+            BOOST_ASSERT(!this->has_result());
+            this->set(this->Accumulator::result(args));
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return this->has_result() ? this->get() : this->Accumulator::result(args);
+        }
+
+    private:
+        with_cached_result &operator =(with_cached_result const &);
+
+        void set(result_type const &result)
+        {
+            ::new(this->cache.address()) result_type(result);
+        }
+
+        result_type const &get() const
+        {
+            return *static_cast<result_type const *>(this->cache.address());
+        }
+
+        bool has_result() const
+        {
+            typedef with_cached_result<Accumulator> this_type;
+            typedef droppable_accumulator_base<this_type> derived_type;
+            return static_cast<derived_type const *>(this)->is_dropped();
+        }
+
+        aligned_storage<sizeof(result_type)> cache;
+    };
+
+    namespace tag
+    {
+        template<typename Feature>
+        struct as_droppable
+        {
+            typedef droppable<Feature> type;
+        };
+
+        template<typename Feature>
+        struct as_droppable<droppable<Feature> >
+        {
+            typedef droppable<Feature> type;
+        };
+
+        //////////////////////////////////////////////////////////////////////////
+        // droppable
+        template<typename Feature>
+        struct droppable
+          : as_feature<Feature>::type
+        {
+            typedef typename as_feature<Feature>::type feature_type;
+            typedef typename feature_type::dependencies tmp_dependencies_;
+
+            typedef 
+                typename mpl::transform<
+                    typename feature_type::dependencies
+                  , as_droppable<mpl::_1>
+                >::type
+            dependencies;
+
+            struct impl
+            {
+                template<typename Sample, typename Weight>
+                struct apply
+                {
+                    typedef
+                        droppable_accumulator<
+                            typename mpl::apply2<typename feature_type::impl, Sample, Weight>::type
+                        >
+                    type;
+                };
+            };
+        };
+    }
+
+    // make droppable<tag::feature(modifier)> work
+    template<typename Feature>
+    struct as_feature<tag::droppable<Feature> >
+    {
+        typedef tag::droppable<typename as_feature<Feature>::type> type;
+    };
+
+    // make droppable<tag::mean> work with non-void weights (should become
+    // droppable<tag::weighted_mean>
+    template<typename Feature>
+    struct as_weighted_feature<tag::droppable<Feature> >
+    {
+        typedef tag::droppable<typename as_weighted_feature<Feature>::type> type;
+    };
+
+    // for the purposes of feature-based dependency resolution,
+    // droppable<Foo> provides the same feature as Foo
+    template<typename Feature>
+    struct feature_of<tag::droppable<Feature> >
+      : feature_of<Feature>
+    {
+    };
+
+    // Note: Usually, the extractor is pulled into the accumulators namespace with
+    // a using directive, not the tag. But the droppable<> feature doesn't have an
+    // extractor, so we can put the droppable tag in the accumulators namespace
+    // without fear of a name conflict.
+    using tag::droppable;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/accumulators/external_accumulator.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/accumulators/external_accumulator.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,108 @@
+///////////////////////////////////////////////////////////////////////////////
+// external_accumulator.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_EXTERNAL_ACCUMULATOR_HPP_EAN_01_12_2005
+#define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_EXTERNAL_ACCUMULATOR_HPP_EAN_01_12_2005
+
+#include <boost/mpl/placeholders.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/depends_on.hpp> // for feature_tag
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/accumulators/reference_accumulator.hpp>
+
+namespace boost { namespace accumulators { namespace impl
+{
+
+    //////////////////////////////////////////////////////////////////////////
+    // external_impl
+    /// INTERNAL ONLY
+    ///
+    template<typename Accumulator, typename Tag>
+    struct external_impl
+      : accumulator_base
+    {
+        typedef typename Accumulator::result_type result_type;
+        typedef typename detail::feature_tag<Accumulator>::type feature_tag;
+
+        external_impl(dont_care) {}
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return this->extract_(args, args[parameter::keyword<Tag>::get() | 0]);
+        }
+
+    private:
+
+        template<typename Args>
+        static result_type extract_(Args const &args, int)
+        {
+            // No named parameter passed to the extractor. Maybe the external
+            // feature is held by reference<>.
+            extractor<feature_tag> extract;
+            return extract(reference_tag<Tag>(args));
+        }
+
+        template<typename Args, typename AccumulatorSet>
+        static result_type extract_(Args const &, AccumulatorSet const &acc)
+        {
+            // OK, a named parameter for this external feature was passed to the
+            // extractor, so use that.
+            extractor<feature_tag> extract;
+            return extract(acc);
+        }
+    };
+
+} // namespace impl
+
+namespace tag
+{
+    //////////////////////////////////////////////////////////////////////////
+    // external
+    template<typename Feature, typename Tag, typename AccumulatorSet>
+    struct external
+      : depends_on<reference<AccumulatorSet, Tag> >
+    {
+        typedef
+            accumulators::impl::external_impl<
+                detail::to_accumulator<Feature, mpl::_1, mpl::_2>
+              , Tag
+            >
+        impl;
+    };
+
+    template<typename Feature, typename Tag>
+    struct external<Feature, Tag, void>
+      : depends_on<>
+    {
+        typedef
+            accumulators::impl::external_impl<
+                detail::to_accumulator<Feature, mpl::_1, mpl::_2>
+              , Tag
+            >
+        impl;
+    };
+}
+
+// for the purposes of feature-based dependency resolution,
+// external_accumulator<Feature, Tag> provides the same feature as Feature
+template<typename Feature, typename Tag, typename AccumulatorSet>
+struct feature_of<tag::external<Feature, Tag, AccumulatorSet> >
+  : feature_of<Feature>
+{
+};
+
+// Note: Usually, the extractor is pulled into the accumulators namespace with
+// a using directive, not the tag. But the external<> feature doesn't have an
+// extractor, so we can put the external tag in the accumulators namespace
+// without fear of a name conflict.
+using tag::external;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/accumulators/reference_accumulator.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/accumulators/reference_accumulator.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,89 @@
+///////////////////////////////////////////////////////////////////////////////
+// reference_accumulator.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_REFERENCE_ACCUMULATOR_HPP_EAN_03_23_2006
+#define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_REFERENCE_ACCUMULATOR_HPP_EAN_03_23_2006
+
+#include <boost/ref.hpp>
+#include <boost/mpl/always.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/accumulators/framework/depends_on.hpp> // for feature_tag
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    //////////////////////////////////////////////////////////////////////////
+    // reference_accumulator_impl
+    //
+    template<typename Referent, typename Tag>
+    struct reference_accumulator_impl
+      : accumulator_base
+    {
+        typedef Referent &result_type;
+
+        template<typename Args>
+        reference_accumulator_impl(Args const &args)
+          : ref(args[parameter::keyword<Tag>::get()])
+        {
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->ref;
+        }
+
+    private:
+        reference_wrapper<Referent> ref;
+    };
+} // namespace impl
+
+namespace tag
+{
+    //////////////////////////////////////////////////////////////////////////
+    // reference_tag
+    template<typename Tag>
+    struct reference_tag
+    {
+    };
+
+    //////////////////////////////////////////////////////////////////////////
+    // reference
+    template<typename Referent, typename Tag>
+    struct reference
+      : depends_on<>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef mpl::always<accumulators::impl::reference_accumulator_impl<Referent, Tag> > impl;
+    };
+}
+
+namespace extract
+{
+    BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, reference, (typename)(typename))
+    BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, reference_tag, (typename))
+}
+
+using extract::reference;
+using extract::reference_tag;
+
+// Map all reference<V,T> features to reference_tag<T> so 
+// that references can be extracted using reference_tag<T>
+// without specifying the referent type.
+template<typename ValueType, typename Tag>
+struct feature_of<tag::reference<ValueType, Tag> >
+  : feature_of<tag::reference_tag<Tag> >
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/accumulators/value_accumulator.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/accumulators/value_accumulator.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,89 @@
+///////////////////////////////////////////////////////////////////////////////
+// value_accumulator.hpp
+//
+//  Copyright 2005 Eric Niebler, Daniel Egloff. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_VALUE_ACCUMULATOR_HPP_EAN_03_23_2006
+#define BOOST_ACCUMULATORS_FRAMEWORK_ACCUMULATORS_VALUE_ACCUMULATOR_HPP_EAN_03_23_2006
+
+#include <boost/mpl/always.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/accumulators/framework/depends_on.hpp> // for feature_tag
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+
+    //////////////////////////////////////////////////////////////////////////
+    // value_accumulator_impl
+    template<typename ValueType, typename Tag>
+    struct value_accumulator_impl
+      : accumulator_base
+    {
+        typedef ValueType result_type;
+
+        template<typename Args>
+        value_accumulator_impl(Args const &args)
+          : val(args[parameter::keyword<Tag>::get()])
+        {
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->val;
+        }
+
+    private:
+        ValueType val;
+    };
+
+} // namespace impl
+
+namespace tag
+{
+    //////////////////////////////////////////////////////////////////////////
+    // value_tag
+    template<typename Tag>
+    struct value_tag
+    {
+    };
+
+    //////////////////////////////////////////////////////////////////////////
+    // value
+    template<typename ValueType, typename Tag>
+    struct value
+      : depends_on<>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef mpl::always<accumulators::impl::value_accumulator_impl<ValueType, Tag> > impl;
+    };
+}
+
+namespace extract
+{
+    BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, value, (typename)(typename))
+    BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, value_tag, (typename))
+}
+
+using extract::value;
+using extract::value_tag;
+
+// Map all value<V,T> features to value_tag<T> so 
+// that values can be extracted using value_tag<T>
+// without specifying the value type.
+template<typename ValueType, typename Tag>
+struct feature_of<tag::value<ValueType, Tag> >
+  : feature_of<tag::value_tag<Tag> >
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/depends_on.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/depends_on.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,411 @@
+///////////////////////////////////////////////////////////////////////////////
+// depends_on.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_DEPENDS_ON_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_FRAMEWORK_DEPENDS_ON_HPP_EAN_28_10_2005
+
+#include <boost/version.hpp>
+#include <boost/mpl/end.hpp>
+#include <boost/mpl/map.hpp>
+#include <boost/mpl/fold.hpp>
+#include <boost/mpl/size.hpp>
+#include <boost/mpl/sort.hpp>
+#include <boost/mpl/insert.hpp>
+#include <boost/mpl/assert.hpp>
+#include <boost/mpl/remove.hpp>
+#include <boost/mpl/vector.hpp>
+#include <boost/mpl/inherit.hpp>
+#include <boost/mpl/identity.hpp>
+#include <boost/mpl/equal_to.hpp>
+#include <boost/mpl/contains.hpp>
+#include <boost/mpl/transform.hpp>
+#include <boost/mpl/is_sequence.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/mpl/insert_range.hpp>
+#include <boost/mpl/transform_view.hpp>
+#include <boost/mpl/inherit_linearly.hpp>
+#include <boost/type_traits/is_base_and_derived.hpp>
+#include <boost/preprocessor/repetition/repeat.hpp>
+#include <boost/preprocessor/repetition/enum_params.hpp>
+#include <boost/preprocessor/facilities/intercept.hpp>
+#include <boost/accumulators/accumulators_fwd.hpp>
+#include <boost/fusion/include/next.hpp>
+#include <boost/fusion/include/equal_to.hpp>
+#include <boost/fusion/include/value_of.hpp>
+#include <boost/fusion/include/mpl.hpp>
+#include <boost/fusion/include/end.hpp>
+#include <boost/fusion/include/begin.hpp>
+#include <boost/fusion/include/cons.hpp>
+
+namespace boost { namespace accumulators
+{
+    ///////////////////////////////////////////////////////////////////////////
+    // as_feature
+    template<typename Feature>
+    struct as_feature
+    {
+        typedef Feature type;
+    };
+
+    ///////////////////////////////////////////////////////////////////////////
+    // weighted_feature
+    template<typename Feature>
+    struct as_weighted_feature
+    {
+        typedef Feature type;
+    };
+
+    ///////////////////////////////////////////////////////////////////////////
+    // feature_of
+    template<typename Feature>
+    struct feature_of
+    {
+        typedef Feature type;
+    };
+
+    namespace detail 
+    {
+        ///////////////////////////////////////////////////////////////////////////
+        // feature_tag
+        template<typename Accumulator>
+        struct feature_tag
+        {
+            typedef typename Accumulator::feature_tag type;
+        };
+
+        template<typename Feature>
+        struct undroppable
+        {
+            typedef Feature type;
+        };
+
+        template<typename Feature>
+        struct undroppable<tag::droppable<Feature> >
+        {
+            typedef Feature type;
+        };
+
+        // For the purpose of determining whether one feature depends on another,
+        // disregard whether the feature is droppable or not.
+        template<typename A, typename B>
+        struct is_dependent_on
+          : is_base_and_derived<
+                typename undroppable<B>::type
+              , typename undroppable<A>::type
+            >
+        {};
+
+        template<typename Features>
+        struct depends_on_base
+          : mpl::inherit_linearly<
+                typename mpl::sort<Features, is_dependent_on<mpl::_1, mpl::_2> >::type
+                // Don't inherit multiply from a feature
+              , mpl::if_<
+                    is_dependent_on<mpl::_1, mpl::_2>
+                  , mpl::_1
+                  , mpl::inherit<mpl::_1, mpl::_2>
+                >
+            >::type
+        {
+        };
+    }
+
+    ///////////////////////////////////////////////////////////////////////////
+    /// depends_on
+    template<BOOST_PP_ENUM_PARAMS(BOOST_ACCUMULATORS_MAX_FEATURES, typename Feature)>
+    struct depends_on
+      : detail::depends_on_base<
+            typename mpl::transform<
+                mpl::vector<BOOST_PP_ENUM_PARAMS(BOOST_ACCUMULATORS_MAX_FEATURES, Feature)>
+              , as_feature<mpl::_1>
+            >::type
+        >
+    {
+        typedef mpl::false_ is_weight_accumulator;
+        typedef
+            typename mpl::transform<
+                mpl::vector<BOOST_PP_ENUM_PARAMS(BOOST_ACCUMULATORS_MAX_FEATURES, Feature)>
+              , as_feature<mpl::_1>
+            >::type
+        dependencies;
+    };
+
+    namespace detail
+    {
+        template<typename Feature>
+        struct matches_feature
+        {
+            template<typename Accumulator>
+            struct apply
+              : is_same<
+                    typename feature_of<typename as_feature<Feature>::type>::type
+                  , typename feature_of<typename as_feature<typename feature_tag<Accumulator>::type>::type>::type
+                >
+            {};
+        };
+
+        template<typename Features, typename Accumulator>
+        struct contains_feature_of
+        {
+            typedef
+                mpl::transform_view<Features, feature_of<as_feature<mpl::_> > >
+            features_list;
+
+            typedef
+                typename feature_of<typename feature_tag<Accumulator>::type>::type
+            the_feature;
+
+            typedef
+                typename mpl::contains<features_list, the_feature>::type
+            type;
+        };
+
+        // This is to work around a bug in early versions of Fusion which caused
+        // a compile error if contains_feature_of<List, mpl::_> is used as a 
+        // predicate to fusion::find_if
+        template<typename Features>
+        struct contains_feature_of_
+        {
+            template<typename Accumulator>
+            struct apply
+              : contains_feature_of<Features, Accumulator>
+            {};
+        };
+
+        template<
+            typename First
+          , typename Last
+          , bool is_empty = fusion::result_of::equal_to<First, Last>::value
+        >
+        struct build_acc_list;
+
+        template<typename First, typename Last>
+        struct build_acc_list<First, Last, true>
+        {
+            typedef fusion::nil type;
+            
+            template<typename Args>
+            static fusion::nil
+            call(Args const &, First const&, Last const&)
+            {
+                return fusion::nil();
+            }
+        };
+
+        template<typename First, typename Last>
+        struct build_acc_list<First, Last, false>
+        {
+            typedef
+                build_acc_list<typename fusion::result_of::next<First>::type, Last>
+            next_build_acc_list;
+
+            typedef fusion::cons<
+                typename fusion::result_of::value_of<First>::type
+              , typename next_build_acc_list::type> 
+            type;
+
+            template<typename Args>
+            static type
+            call(Args const &args, First const& f, Last const& l)
+            {
+                return type(args, next_build_acc_list::call(args, fusion::next(f), l));
+            }
+        };
+
+        namespace meta
+        {
+            template<typename Sequence>
+            struct make_acc_list
+              : build_acc_list<
+                    typename fusion::result_of::begin<Sequence>::type
+                  , typename fusion::result_of::end<Sequence>::type
+                >
+            {};
+        }
+
+        template<typename Sequence, typename Args>
+        typename meta::make_acc_list<Sequence>::type
+        make_acc_list(Sequence const &seq, Args const &args)
+        {
+            return meta::make_acc_list<Sequence>::call(args, fusion::begin(seq), fusion::end(seq));
+        }
+
+        ///////////////////////////////////////////////////////////////////////////
+        // checked_as_weighted_feature
+        template<typename Feature>
+        struct checked_as_weighted_feature
+        {
+            typedef typename as_feature<Feature>::type feature_type;
+            typedef typename as_weighted_feature<feature_type>::type type;
+            // weighted and non-weighted flavors should provide the same feature.
+            BOOST_MPL_ASSERT((
+                is_same<
+                    typename feature_of<feature_type>::type
+                  , typename feature_of<type>::type
+                >
+            ));
+        };
+
+        ///////////////////////////////////////////////////////////////////////////
+        // as_feature_list
+        template<typename Features, typename Weight>
+        struct as_feature_list
+          : mpl::transform_view<Features, checked_as_weighted_feature<mpl::_1> >
+        {
+        };
+
+        template<typename Features>
+        struct as_feature_list<Features, void>
+          : mpl::transform_view<Features, as_feature<mpl::_1> >
+        {
+        };
+
+        ///////////////////////////////////////////////////////////////////////////
+        // accumulator_wrapper
+        template<typename Accumulator, typename Feature>
+        struct accumulator_wrapper
+          : Accumulator
+        {
+            typedef Feature feature_tag;
+
+            accumulator_wrapper(accumulator_wrapper const &that)
+              : Accumulator(*static_cast<Accumulator const *>(&that))
+            {
+            }
+
+            template<typename Args>
+            accumulator_wrapper(Args const &args)
+              : Accumulator(args)
+            {
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////
+        // to_accumulator
+        template<typename Feature, typename Sample, typename Weight>
+        struct to_accumulator
+        {
+            typedef
+                accumulator_wrapper<
+                    typename mpl::apply2<typename Feature::impl, Sample, Weight>::type
+                  , Feature
+                >
+            type;
+        };
+
+        template<typename Feature, typename Sample, typename Weight, typename Tag, typename AccumulatorSet>
+        struct to_accumulator<Feature, Sample, tag::external<Weight, Tag, AccumulatorSet> >
+        {
+            BOOST_MPL_ASSERT((is_same<Tag, void>));
+            BOOST_MPL_ASSERT((is_same<AccumulatorSet, void>));
+
+            typedef
+                accumulator_wrapper<
+                    typename mpl::apply2<typename Feature::impl, Sample, Weight>::type
+                  , Feature
+                >
+            accumulator_type;
+
+            typedef
+                typename mpl::if_<
+                    typename Feature::is_weight_accumulator
+                  , accumulator_wrapper<impl::external_impl<accumulator_type, tag::weights>, Feature>
+                  , accumulator_type
+                >::type
+            type;
+        };
+
+        // BUGBUG work around a MPL bug wrt map insertion
+        template<typename FeatureMap, typename Feature>
+        struct insert_feature
+          : mpl::eval_if<
+                mpl::has_key<FeatureMap, typename feature_of<Feature>::type>
+              , mpl::identity<FeatureMap>
+              , mpl::insert<FeatureMap, mpl::pair<typename feature_of<Feature>::type, Feature> >
+            >
+        {
+        };
+
+        template<typename FeatureMap, typename Feature, typename Weight>
+        struct insert_dependencies
+          : mpl::fold<
+                as_feature_list<typename Feature::dependencies, Weight>
+              , FeatureMap
+              , insert_dependencies<
+                    insert_feature<mpl::_1, mpl::_2>
+                  , mpl::_2
+                  , Weight
+                >
+            >
+        {
+        };
+
+        template<typename FeatureMap, typename Features, typename Weight>
+        struct insert_sequence
+          : mpl::fold< // BUGBUG should use insert_range, but doesn't seem to work for maps
+                as_feature_list<Features, Weight>
+              , FeatureMap
+              , insert_feature<mpl::_1, mpl::_2>
+            >
+        {
+        };
+
+        template<typename Features, typename Sample, typename Weight>
+        struct make_accumulator_tuple
+        {
+            typedef
+                typename mpl::fold<
+                    as_feature_list<Features, Weight>
+                  , mpl::map0<>
+                  , mpl::if_<
+                        mpl::is_sequence<mpl::_2>
+                      , insert_sequence<mpl::_1, mpl::_2, Weight>
+                      , insert_feature<mpl::_1, mpl::_2>
+                    >
+                >::type
+            feature_map;
+
+            // for each element in the map, add its dependencies also
+            typedef
+                typename mpl::fold<
+                    feature_map
+                  , feature_map
+                  , insert_dependencies<mpl::_1, mpl::second<mpl::_2>, Weight>
+                >::type
+            feature_map_with_dependencies;
+
+            // turn the map into a vector so we can sort it
+            typedef
+                typename mpl::insert_range<
+                    mpl::vector<>
+                  , mpl::end<mpl::vector<> >::type
+                  , mpl::transform_view<feature_map_with_dependencies, mpl::second<mpl::_1> >
+                >::type
+            feature_vector_with_dependencies;
+
+            // sort the features according to which is derived from which
+            typedef
+                typename mpl::sort<
+                    feature_vector_with_dependencies
+                  , is_dependent_on<mpl::_2, mpl::_1>
+                >::type
+            sorted_feature_vector;
+
+            // From the vector of features, construct a vector of accumulators
+            typedef
+                typename mpl::transform<
+                    sorted_feature_vector
+                  , to_accumulator<mpl::_1, Sample, Weight>
+                >::type
+            type;
+        };
+
+    } // namespace detail
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/external.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/external.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,27 @@
+///////////////////////////////////////////////////////////////////////////////
+// external.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_EXTERNAL_HPP_EAN_01_12_2005
+#define BOOST_ACCUMULATORS_FRAMEWORK_EXTERNAL_HPP_EAN_01_12_2005
+
+#include <boost/mpl/apply.hpp>
+#include <boost/accumulators/framework/accumulators/external_accumulator.hpp>
+
+//namespace boost { namespace accumulators
+//{
+//
+/////////////////////////////////////////////////////////////////////////////////
+//// external
+////
+//template<typename Type>
+//struct external
+//{
+//};
+//
+//}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/extractor.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/extractor.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,229 @@
+///////////////////////////////////////////////////////////////////////////////
+// extractor.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_EXTRACTOR_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_FRAMEWORK_EXTRACTOR_HPP_EAN_28_10_2005
+
+#include <boost/preprocessor/tuple/rem.hpp>
+#include <boost/preprocessor/array/size.hpp>
+#include <boost/preprocessor/array/data.hpp>
+#include <boost/preprocessor/array/elem.hpp>
+#include <boost/preprocessor/seq/to_array.hpp>
+#include <boost/preprocessor/seq/transform.hpp>
+#include <boost/preprocessor/repetition/enum_params.hpp>
+#include <boost/preprocessor/repetition/enum_trailing_params.hpp>
+#include <boost/preprocessor/repetition/enum_trailing_binary_params.hpp>
+#include <boost/parameter/binding.hpp>
+#include <boost/mpl/apply.hpp>
+#include <boost/mpl/eval_if.hpp>
+#include <boost/type_traits/remove_reference.hpp>
+#include <boost/accumulators/accumulators_fwd.hpp>
+#include <boost/accumulators/framework/parameters/accumulator.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace detail
+{
+    template<typename AccumulatorSet, typename Feature>
+    struct accumulator_set_result
+    {
+        typedef typename as_feature<Feature>::type feature_type;
+        typedef typename mpl::apply<AccumulatorSet, feature_type>::type::result_type type;
+    };
+
+    template<typename Args, typename Feature>
+    struct argument_pack_result
+      : accumulator_set_result<
+            typename remove_reference<
+                typename parameter::binding<Args, tag::accumulator>::type
+            >::type
+          , Feature
+        >
+    {
+    };
+
+    template<typename A, typename Feature>
+    struct extractor_result
+      : mpl::eval_if<
+            detail::is_accumulator_set<A>
+          , accumulator_set_result<A, Feature>
+          , argument_pack_result<A, Feature>
+        >
+    {
+    };
+
+    template<typename Feature, typename AccumulatorSet>
+    typename extractor_result<AccumulatorSet, Feature>::type
+    do_extract(AccumulatorSet const &acc, mpl::true_)
+    {
+        typedef typename as_feature<Feature>::type feature_type;
+        return extract_result<feature_type>(acc);
+    }
+
+    template<typename Feature, typename Args>
+    typename extractor_result<Args, Feature>::type
+    do_extract(Args const &args, mpl::false_)
+    {
+        typedef typename as_feature<Feature>::type feature_type;
+        return find_accumulator<feature_type>(args[accumulator]).result(args);
+    }
+
+} // namespace detail
+
+
+///////////////////////////////////////////////////////////////////////////////
+/// Extracts the result associated with Feature from the specified accumulator_set.
+template<typename Feature>
+struct extractor
+{
+    typedef extractor<Feature> this_type;
+
+    /// The result meta-function for determining the return type of the extractor
+    template<typename F>
+    struct result;
+
+    template<typename A1>
+    struct result<this_type(A1)>
+      : detail::extractor_result<A1, Feature>
+    {
+    };
+
+    /// Extract the result associated with Feature from the accumulator set
+    /// \param acc The accumulator set object from which to extract the result
+    template<typename Arg1>
+    typename detail::extractor_result<Arg1, Feature>::type
+    operator ()(Arg1 const &arg1) const
+    {
+        // Arg1 could be an accumulator_set or an argument pack containing 
+        // an accumulator_set. Dispatch accordingly.
+        return detail::do_extract<Feature>(arg1, detail::is_accumulator_set<Arg1>());
+    }
+
+    /// \overload
+    ///
+    /// \param a1 Optional named parameter to be passed to the accumulator's result() function.
+    template<typename AccumulatorSet, typename A1>
+    typename detail::extractor_result<AccumulatorSet, Feature>::type
+    operator ()(AccumulatorSet const &acc, A1 const &a1) const
+    {
+        BOOST_MPL_ASSERT((detail::is_accumulator_set<AccumulatorSet>));
+        typedef typename as_feature<Feature>::type feature_type;
+        return extract_result<feature_type>(acc, a1);
+    }
+
+    // ... other overloads generated by Boost.Preprocessor:
+
+    /// INTERNAL ONLY
+    ///
+#define BOOST_ACCUMULATORS_EXTRACTOR_FUN_OP(z, n, _)                                    \
+    template<BOOST_PP_ENUM_PARAMS_Z(z, n, typename A)>                                  \
+    struct result<this_type(BOOST_PP_ENUM_PARAMS_Z(z, n, A))>                           \
+      : detail::extractor_result<A1, Feature>                                           \
+    {};                                                                                 \
+    template<                                                                           \
+        typename AccumulatorSet                                                         \
+        BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, typename A)                               \
+    >                                                                                   \
+    typename detail::extractor_result<AccumulatorSet, Feature>::type                    \
+    operator ()(                                                                        \
+        AccumulatorSet const &acc                                                       \
+        BOOST_PP_ENUM_TRAILING_BINARY_PARAMS_Z(z, n, A, const &a)                       \
+    ) const                                                                             \
+    {                                                                                   \
+        BOOST_MPL_ASSERT((detail::is_accumulator_set<AccumulatorSet>));                 \
+        typedef typename as_feature<Feature>::type feature_type;                        \
+        return extract_result<feature_type>(acc BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, a));\
+    }
+
+    BOOST_PP_REPEAT_FROM_TO(
+        2
+      , BOOST_PP_INC(BOOST_ACCUMULATORS_MAX_ARGS)
+      , BOOST_ACCUMULATORS_EXTRACTOR_FUN_OP
+      , _
+    )
+
+    #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED
+    /// \overload
+    ///
+    template<typename AccumulatorSet, typename A1, typename A2, ...>
+    typename detail::extractor_result<AccumulatorSet, Feature>::type
+    operator ()(AccumulatorSet const &acc, A1 const &a1, A2 const &a2, ...);
+    #endif
+};
+
+/// INTERNAL ONLY
+///
+#define BOOST_ACCUMULATORS_ARRAY_REM(Array)                                                         \
+    BOOST_PP_TUPLE_REM_CTOR(BOOST_PP_ARRAY_SIZE(Array), BOOST_PP_ARRAY_DATA(Array))
+
+/// INTERNAL ONLY
+///
+#define BOOST_ACCUMULATORS_SEQ_REM(Seq)                                                             \
+    BOOST_ACCUMULATORS_ARRAY_REM(BOOST_PP_SEQ_TO_ARRAY(Seq))
+
+/// INTERNAL ONLY
+///
+#define BOOST_ACCUMULATORS_ARGS_OP(s, data, elem)                                                   \
+    T ## s
+
+/// INTERNAL ONLY
+///
+#define BOOST_ACCUMULATORS_PARAMS_OP(s, data, elem)                                                 \
+    elem T ## s
+
+/// INTERNAL ONLY
+///
+#define BOOST_ACCUMULATORS_MAKE_FEATURE(Tag, Feature, ParamsSeq)                                    \
+    Tag::Feature<                                                                                   \
+        BOOST_ACCUMULATORS_SEQ_REM(                                                                 \
+            BOOST_PP_SEQ_TRANSFORM(BOOST_ACCUMULATORS_ARGS_OP, ~, ParamsSeq)                        \
+        )                                                                                           \
+    >
+
+/// INTERNAL ONLY
+///
+#define BOOST_ACCUMULATORS_DEFINE_EXTRACTOR_FUN_IMPL(z, n, Tag, Feature, ParamsSeq)                 \
+    template<                                                                                       \
+        BOOST_ACCUMULATORS_SEQ_REM(                                                                 \
+            BOOST_PP_SEQ_TRANSFORM(BOOST_ACCUMULATORS_PARAMS_OP, ~, ParamsSeq)                      \
+        )                                                                                           \
+      , typename Arg1                                                                               \
+        BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, typename A)                                           \
+    >                                                                                               \
+    typename boost::accumulators::detail::extractor_result<                                         \
+        Arg1                                                                                        \
+      , BOOST_ACCUMULATORS_MAKE_FEATURE(Tag, Feature, ParamsSeq)                                    \
+    >::type                                                                                         \
+    Feature(Arg1 const &arg1 BOOST_PP_ENUM_TRAILING_BINARY_PARAMS_Z(z, n, A, const &a) )            \
+    {                                                                                               \
+        typedef BOOST_ACCUMULATORS_MAKE_FEATURE(Tag, Feature, ParamsSeq) feature_type;              \
+        return boost::accumulators::extractor<feature_type>()(                                      \
+            arg1 BOOST_PP_ENUM_TRAILING_PARAMS_Z(z, n, a));                                         \
+    }
+
+/// INTERNAL ONLY
+///
+#define BOOST_ACCUMULATORS_DEFINE_EXTRACTOR_FUN(z, n, _)                                            \
+    BOOST_ACCUMULATORS_DEFINE_EXTRACTOR_FUN_IMPL(                                                   \
+        z                                                                                           \
+      , n                                                                                           \
+      , BOOST_PP_ARRAY_ELEM(0, _)                                                                   \
+      , BOOST_PP_ARRAY_ELEM(1, _)                                                                   \
+      , BOOST_PP_ARRAY_ELEM(2, _)                                                                   \
+    )
+
+#define BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(Tag, Feature, ParamSeq)                                 \
+    BOOST_PP_REPEAT(                                                                                \
+        BOOST_PP_INC(BOOST_ACCUMULATORS_MAX_ARGS)                                                   \
+      , BOOST_ACCUMULATORS_DEFINE_EXTRACTOR_FUN                                                     \
+      , (3, (Tag, Feature, ParamSeq))                                                               \
+    )
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/features.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/features.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,29 @@
+///////////////////////////////////////////////////////////////////////////////
+// features.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_STATS_HPP_EAN_08_12_2005
+#define BOOST_ACCUMULATORS_STATISTICS_STATS_HPP_EAN_08_12_2005
+
+#include <boost/preprocessor/repetition/enum_params.hpp>
+#include <boost/mpl/vector.hpp>
+#include <boost/accumulators/accumulators_fwd.hpp>
+
+namespace boost { namespace accumulators
+{
+
+///////////////////////////////////////////////////////////////////////////////
+// features
+//
+template<BOOST_PP_ENUM_PARAMS(BOOST_ACCUMULATORS_MAX_FEATURES, typename Feature)>
+struct features
+  : mpl::vector<BOOST_PP_ENUM_PARAMS(BOOST_ACCUMULATORS_MAX_FEATURES, Feature)>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/parameters/accumulator.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/parameters/accumulator.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,20 @@
+///////////////////////////////////////////////////////////////////////////////
+// accumulator.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_ACCUMULATOR_HPP_EAN_31_10_2005
+#define BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_ACCUMULATOR_HPP_EAN_31_10_2005
+
+#include <boost/parameter/keyword.hpp>
+
+namespace boost { namespace accumulators
+{
+
+BOOST_PARAMETER_KEYWORD(tag, accumulator)
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/parameters/sample.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/parameters/sample.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,20 @@
+///////////////////////////////////////////////////////////////////////////////
+// sample.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_SAMPLE_HPP_EAN_31_10_2005
+#define BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_SAMPLE_HPP_EAN_31_10_2005
+
+#include <boost/parameter/keyword.hpp>
+
+namespace boost { namespace accumulators
+{
+
+BOOST_PARAMETER_KEYWORD(tag, sample)
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/parameters/weight.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/parameters/weight.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,21 @@
+///////////////////////////////////////////////////////////////////////////////
+// weight.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_WEIGHT_HPP_EAN_31_10_2005
+#define BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_WEIGHT_HPP_EAN_31_10_2005
+
+#include <boost/parameter/keyword.hpp>
+
+namespace boost { namespace accumulators
+{
+
+// The weight of a single sample
+BOOST_PARAMETER_KEYWORD(tag, weight)
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/framework/parameters/weights.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/framework/parameters/weights.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,21 @@
+///////////////////////////////////////////////////////////////////////////////
+// weights.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_WEIGHTS_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_FRAMEWORK_PARAMETERS_WEIGHTS_HPP_EAN_28_10_2005
+
+#include <boost/parameter/keyword.hpp>
+
+namespace boost { namespace accumulators
+{
+
+// The weight accumulator
+BOOST_PARAMETER_KEYWORD(tag, weights)
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/numeric/detail/function1.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/numeric/detail/function1.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,75 @@
+// Copyright David Abrahams 2006. Distributed under the Boost
+// Software License, Version 1.0. (See accompanying
+// file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+#ifndef BOOST_DETAIL_FUNCTION1_DWA200655_HPP
+# define BOOST_DETAIL_FUNCTION1_DWA200655_HPP
+
+# include <boost/concept_check.hpp>
+# include <boost/type_traits/remove_reference.hpp>
+# include <boost/type_traits/add_const.hpp>
+# include <boost/mpl/apply.hpp>
+
+namespace boost { namespace detail {
+
+// A utility for creating unary function objects that play nicely with
+// boost::result_of and that handle the forwarding problem.
+//
+// mpl::apply<F, A0>::type is expected to be a stateless function
+// object that accepts an argument of type A0&.  It is also expected
+// to have a nested ::result_type identical to its return type.
+template<typename F>
+struct function1
+{
+    template<typename Signature>
+    struct result
+    {};
+
+    template<typename This, typename A0>
+    struct result<This(A0)>
+    {
+        // How adding const to arguments handles rvalues.
+        //
+        // if A0 is     arg0 is       represents actual argument
+        // --------     -------       --------------------------
+        // T const &    T const       const T lvalue
+        // T &          T             non-const T lvalue
+        // T const      T const       const T rvalue
+        // T            T const       non-const T rvalue
+        typedef typename remove_reference<
+            typename add_const< A0 >::type
+        >::type arg0;
+
+        typedef typename mpl::apply1<F, arg0>::type impl;
+        typedef typename impl::result_type type;
+    };
+
+    // Handles mutable lvalues
+    template<typename A0>
+    typename result<function1(A0 &)>::type
+    operator ()(A0 &a0) const
+    {
+        typedef typename result<function1(A0 &)>::impl impl;
+        typedef typename result<function1(A0 &)>::type type;
+        typedef A0 &arg0;
+        BOOST_CONCEPT_ASSERT((UnaryFunction<impl, type, arg0>));
+        //boost::function_requires<UnaryFunctionConcept<impl, type, arg0> >();
+        return impl()(a0);
+    }
+
+    // Handles const lvalues and all rvalues
+    template<typename A0>
+    typename result<function1(A0 const &)>::type
+    operator ()(A0 const &a0) const
+    {
+        typedef typename result<function1(A0 const &)>::impl impl;
+        typedef typename result<function1(A0 const &)>::type type;
+        typedef A0 const &arg0;
+        BOOST_CONCEPT_ASSERT((UnaryFunction<impl, type, arg0>));
+        //boost::function_requires<UnaryFunctionConcept<impl, type, arg0> >();
+        return impl()(a0);
+    }
+};
+
+}} // namespace boost::detail
+
+#endif // BOOST_DETAIL_FUNCTION1_DWA200655_HPP

Added: trunk/boost/accumulators/numeric/detail/function2.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/numeric/detail/function2.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,10 @@
+// Copyright David Abrahams 2006. Distributed under the Boost
+// Software License, Version 1.0. (See accompanying
+// file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+#ifndef BOOST_DETAIL_FUNCTION2_DWA200655_HPP
+# define BOOST_DETAIL_FUNCTION2_DWA200655_HPP
+
+# define args (2)
+# include <boost/accumulators/numeric/detail/function_n.hpp>
+
+#endif // BOOST_DETAIL_FUNCTION2_DWA200655_HPP

Added: trunk/boost/accumulators/numeric/detail/function3.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/numeric/detail/function3.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,10 @@
+// Copyright David Abrahams 2006. Distributed under the Boost
+// Software License, Version 1.0. (See accompanying
+// file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+#ifndef BOOST_DETAIL_FUNCTION3_DWA2006514_HPP
+# define BOOST_DETAIL_FUNCTION3_DWA2006514_HPP
+
+# define args (3)
+# include <boost/accumulators/numeric/detail/function_n.hpp>
+
+#endif // BOOST_DETAIL_FUNCTION3_DWA2006514_HPP

Added: trunk/boost/accumulators/numeric/detail/function4.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/numeric/detail/function4.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,10 @@
+// Copyright David Abrahams 2006. Distributed under the Boost
+// Software License, Version 1.0. (See accompanying
+// file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+#ifndef BOOST_DETAIL_FUNCTION4_DWA2006514_HPP
+# define BOOST_DETAIL_FUNCTION4_DWA2006514_HPP
+
+# define args (4)
+# include <boost/accumulators/numeric/detail/function_n.hpp>
+
+#endif // BOOST_DETAIL_FUNCTION4_DWA2006514_HPP

Added: trunk/boost/accumulators/numeric/detail/function_n.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/numeric/detail/function_n.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,148 @@
+// Copyright David Abrahams 2006. Distributed under the Boost
+// Software License, Version 1.0. (See accompanying
+// file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+// #include guards intentionally disabled.
+// #ifndef BOOST_DETAIL_FUNCTION_N_DWA2006514_HPP
+// # define BOOST_DETAIL_FUNCTION_N_DWA2006514_HPP
+
+#include <boost/mpl/void.hpp>
+#include <boost/mpl/apply.hpp>
+
+#include <boost/preprocessor/control/if.hpp>
+#include <boost/preprocessor/cat.hpp>
+#include <boost/preprocessor/punctuation/comma_if.hpp>
+#include <boost/preprocessor/repetition/enum_params.hpp>
+#include <boost/preprocessor/repetition/enum_trailing_params.hpp>
+#include <boost/preprocessor/repetition/repeat.hpp>
+#include <boost/preprocessor/seq/fold_left.hpp>
+#include <boost/preprocessor/seq/seq.hpp>
+#include <boost/preprocessor/seq/for_each.hpp>
+#include <boost/preprocessor/seq/for_each_i.hpp>
+#include <boost/preprocessor/seq/for_each_product.hpp>
+#include <boost/preprocessor/seq/size.hpp>
+#include <boost/type_traits/add_const.hpp>
+#include <boost/type_traits/remove_reference.hpp>
+
+namespace boost { namespace detail {
+
+# define BOOST_DETAIL_default_arg(z, n, _)                                      \
+    typedef mpl::void_ BOOST_PP_CAT(arg, n);
+
+# define BOOST_DETAIL_function_arg(z, n, _)                                     \
+    typedef typename remove_reference<                                          \
+        typename add_const< BOOST_PP_CAT(A, n) >::type                          \
+    >::type BOOST_PP_CAT(arg, n);
+
+#define BOOST_DETAIL_cat_arg_counts(s, state, n)                                \
+    BOOST_PP_IF(                                                                \
+        n                                                                       \
+      , BOOST_PP_CAT(state, BOOST_PP_CAT(_, n))                                 \
+      , state                                                                   \
+    )                                                                           \
+    /**/
+
+#define function_name                                                           \
+    BOOST_PP_SEQ_FOLD_LEFT(                                                     \
+        BOOST_DETAIL_cat_arg_counts                                             \
+      , BOOST_PP_CAT(function, BOOST_PP_SEQ_HEAD(args))                         \
+      , BOOST_PP_SEQ_TAIL(args)(0)                                              \
+    )                                                                           \
+    /**/
+
+template<typename F>
+struct function_name
+{
+    BOOST_PP_REPEAT(
+        BOOST_MPL_LIMIT_METAFUNCTION_ARITY
+      , BOOST_DETAIL_default_arg
+      , ~
+    )
+
+    template<typename Signature>
+    struct result {};
+
+#define BOOST_DETAIL_function_result(r, _, n)                                   \
+    template<typename This BOOST_PP_ENUM_TRAILING_PARAMS(n, typename A)>        \
+    struct result<This(BOOST_PP_ENUM_PARAMS(n, A))>                             \
+    {                                                                           \
+        BOOST_PP_REPEAT(n, BOOST_DETAIL_function_arg, ~)                        \
+        typedef                                                                 \
+            typename BOOST_PP_CAT(mpl::apply, BOOST_MPL_LIMIT_METAFUNCTION_ARITY)<\
+                F                                                               \
+                BOOST_PP_ENUM_TRAILING_PARAMS(                                  \
+                    BOOST_MPL_LIMIT_METAFUNCTION_ARITY                          \
+                  , arg                                                         \
+                )                                                               \
+            >::type                                                             \
+        impl;                                                                   \
+        typedef typename impl::result_type type;                                \
+    };                                                                          \
+    /**/
+
+    BOOST_PP_SEQ_FOR_EACH(BOOST_DETAIL_function_result, _, args)
+
+# define arg_type(r, _, i, is_const)                                            \
+    BOOST_PP_COMMA_IF(i) BOOST_PP_CAT(A, i) BOOST_PP_CAT(const_if, is_const) &
+
+# define result_(r, n, constness)                                               \
+    typename result<                                                            \
+        function_name(                                                          \
+            BOOST_PP_SEQ_FOR_EACH_I_R(r, arg_type, ~, constness)                \
+        )                                                                       \
+    >                                                                           \
+    /**/
+
+# define param(r, _, i, is_const) BOOST_PP_COMMA_IF(i)                          \
+    BOOST_PP_CAT(A, i) BOOST_PP_CAT(const_if, is_const) & BOOST_PP_CAT(x, i)
+
+# define param_list(r, n, constness)                                            \
+    BOOST_PP_SEQ_FOR_EACH_I_R(r, param, ~, constness)
+
+# define call_operator(r, constness)                                            \
+    template<BOOST_PP_ENUM_PARAMS(BOOST_PP_SEQ_SIZE(constness), typename A)>    \
+        result_(r, BOOST_PP_SEQ_SIZE(constness), constness)::type               \
+    operator ()( param_list(r, BOOST_PP_SEQ_SIZE(constness), constness) ) const \
+    {                                                                           \
+        typedef result_(r, BOOST_PP_SEQ_SIZE(constness), constness)::impl impl; \
+        return impl()(BOOST_PP_ENUM_PARAMS(BOOST_PP_SEQ_SIZE(constness), x));   \
+    }                                                                           \
+    /**/
+
+# define const_if0
+# define const_if1 const
+
+# define bits(z, n, _) ((0)(1))
+
+# define gen_operator(r, _, n)                                                  \
+    BOOST_PP_SEQ_FOR_EACH_PRODUCT_R(                                            \
+        r                                                                       \
+      , call_operator                                                           \
+      , BOOST_PP_REPEAT(n, bits, ~)                                             \
+    )                                                                           \
+    /**/
+
+    BOOST_PP_SEQ_FOR_EACH(
+        gen_operator
+      , ~
+      , args
+    )
+
+# undef bits
+# undef const_if1
+# undef const_if0
+# undef call_operator
+# undef param_list
+# undef param
+# undef result_
+# undef default_
+# undef arg_type
+# undef gen_operator
+# undef function_name
+
+# undef args
+};
+
+}} // namespace boost::detail
+
+//#endif // BOOST_DETAIL_FUNCTION_N_DWA2006514_HPP

Added: trunk/boost/accumulators/numeric/detail/pod_singleton.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/numeric/detail/pod_singleton.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,20 @@
+// Copyright David Abrahams 2006. Distributed under the Boost
+// Software License, Version 1.0. (See accompanying
+// file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+#ifndef BOOST_DETAIL_POD_SINGLETON_DWA200655_HPP
+# define BOOST_DETAIL_POD_SINGLETON_DWA200655_HPP
+
+namespace boost { namespace detail {
+
+template<typename T>
+struct pod_singleton
+{
+    static T instance;
+};
+
+template<typename T>
+T pod_singleton<T>::instance;
+
+}} // namespace boost::detail
+
+#endif // BOOST_DETAIL_POD_SINGLETON_DWA200655_HPP

Added: trunk/boost/accumulators/numeric/functional.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/numeric/functional.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,470 @@
+///////////////////////////////////////////////////////////////////////////////
+/// \file functional.hpp
+///
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_NUMERIC_FUNCTIONAL_HPP_EAN_08_12_2005
+#define BOOST_NUMERIC_FUNCTIONAL_HPP_EAN_08_12_2005
+
+#include <limits>
+#include <functional>
+#include <boost/mpl/if.hpp>
+#include <boost/mpl/and.hpp>
+#include <boost/type_traits/remove_const.hpp>
+#include <boost/type_traits/add_reference.hpp>
+#include <boost/type_traits/is_empty.hpp>
+#include <boost/type_traits/is_integral.hpp>
+#include <boost/type_traits/is_floating_point.hpp>
+#include <boost/utility/enable_if.hpp>
+#include <boost/typeof/typeof.hpp>
+#include <boost/accumulators/numeric/functional_fwd.hpp>
+#include <boost/accumulators/numeric/detail/function1.hpp>
+#include <boost/accumulators/numeric/detail/function2.hpp>
+#include <boost/accumulators/numeric/detail/pod_singleton.hpp>
+
+#ifdef BOOST_NUMERIC_FUNCTIONAL_STD_VECTOR_SUPPORT
+# include <boost/accumulators/numeric/functional/vector.hpp>
+#endif
+
+#ifdef BOOST_NUMERIC_FUNCTIONAL_STD_VALARRAY_SUPPORT
+# include <boost/accumulators/numeric/functional/valarray.hpp>
+#endif
+
+#ifdef BOOST_NUMERIC_FUNCTIONAL_STD_COMPLEX_SUPPORT
+# include <boost/accumulators/numeric/functional/complex.hpp>
+#endif
+
+/// INTERNAL ONLY
+///
+#define BOOST_NUMERIC_FUNCTIONAL_HPP_INCLUDED
+
+#ifdef BOOST_NUMERIC_FUNCTIONAL_DOXYGEN_INVOKED
+// Hack to make Doxygen show the inheritance relationships
+/// INTERNAL ONLY
+///
+namespace std
+{
+    /// INTERNAL ONLY
+    ///
+    template<class Arg, class Ret> struct unary_function {};
+    /// INTERNAL ONLY
+    ///
+    template<class Left, class Right, class Ret> struct binary_function {};
+}
+#endif
+
+namespace boost { namespace numeric
+{
+    namespace functional
+    {
+        /// INTERNAL ONLY
+        ///
+        template<typename A0, typename A1>
+        struct are_integral
+          : mpl::and_<is_integral<A0>, is_integral<A1> >
+        {};
+
+        template<typename Left, typename Right>
+        struct left_ref
+        {
+            typedef Left &type;
+        };
+    }
+
+    // TODO: handle complex weight, valarray, MTL vectors
+
+    /// INTERNAL ONLY
+    ///
+#define BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP(Name, Op)                                      \
+    namespace functional                                                                        \
+    {                                                                                           \
+        template<typename Arg>                                                                  \
+        struct result_of_ ## Name                                                               \
+        {                                                                                       \
+            BOOST_TYPEOF_NESTED_TYPEDEF_TPL(nested, Op (*(Arg*)0))                              \
+            typedef typename nested::type type;                                                 \
+        };                                                                                      \
+        template<typename Arg, typename EnableIf>                                               \
+        struct Name ## _base                                                                    \
+          : std::unary_function<Arg, typename result_of_ ## Name<Arg>::type>                    \
+        {                                                                                       \
+            typename result_of_ ## Name<Arg>::type operator ()(Arg &arg) const                  \
+            {                                                                                   \
+                return Op arg;                                                                  \
+            }                                                                                   \
+        };                                                                                      \
+        template<typename Arg, typename ArgTag>                                                 \
+        struct Name                                                                             \
+          : Name ## _base<Arg, void>                                                            \
+        {};                                                                                     \
+    }                                                                                           \
+    namespace op                                                                                \
+    {                                                                                           \
+        struct Name                                                                             \
+          : boost::detail::function1<functional::Name<_, functional::tag<_> > >                 \
+        {};                                                                                     \
+    }                                                                                           \
+    namespace                                                                                   \
+    {                                                                                           \
+        op::Name const &Name = boost::detail::pod_singleton<op::Name>::instance;                \
+    }                                                                                           \
+    /**/
+
+    /// INTERNAL ONLY
+    ///
+#define BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(Name, Op, RetType)                            \
+    namespace functional                                                                        \
+    {                                                                                           \
+        template<typename Left, typename Right, typename EnableIf>                              \
+        struct result_of_ ## Name                                                               \
+        {                                                                                       \
+            RetType(Left, Op, Right)                                                            \
+        };                                                                                      \
+        template<typename Left, typename Right, typename EnableIf>                              \
+        struct Name ## _base                                                                    \
+          : std::binary_function<Left, Right, typename result_of_ ## Name<Left, Right>::type>   \
+        {                                                                                       \
+            typename result_of_ ## Name<Left, Right>::type                                      \
+            operator ()(Left &left, Right &right) const                                         \
+            {                                                                                   \
+                return left Op right;                                                           \
+            }                                                                                   \
+        };                                                                                      \
+        template<typename Left, typename Right, typename LeftTag, typename RightTag>            \
+        struct Name                                                                             \
+          : Name ## _base<Left, Right, void>                                                    \
+        {};                                                                                     \
+    }                                                                                           \
+    namespace op                                                                                \
+    {                                                                                           \
+        struct Name                                                                             \
+          : boost::detail::function2<                                                           \
+                functional::Name<_1, _2, functional::tag<_1>, functional::tag<_2> >             \
+            >                                                                                   \
+        {};                                                                                     \
+    }                                                                                           \
+    namespace                                                                                   \
+    {                                                                                           \
+        op::Name const &Name = boost::detail::pod_singleton<op::Name>::instance;                \
+    }                                                                                           \
+    /**/
+
+    /// INTERNAL ONLY
+    ///
+#define BOOST_NUMERIC_FUNCTIONAL_DEDUCED(Left, Op, Right)                                       \
+    BOOST_TYPEOF_NESTED_TYPEDEF_TPL(nested, (*(Left*)0) Op (*(Right*)0))                        \
+    typedef typename nested::type type;                                                         \
+    /**/
+
+    /// INTERNAL ONLY
+    ///
+#define BOOST_NUMERIC_FUNCTIONAL_LEFT(Left, Op, Right)                                          \
+    typedef Left &type;                                                                         \
+    /**/
+
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(plus, +, BOOST_NUMERIC_FUNCTIONAL_DEDUCED)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(minus, -, BOOST_NUMERIC_FUNCTIONAL_DEDUCED)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(multiplies, *, BOOST_NUMERIC_FUNCTIONAL_DEDUCED)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(divides, /, BOOST_NUMERIC_FUNCTIONAL_DEDUCED)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(modulus, %, BOOST_NUMERIC_FUNCTIONAL_DEDUCED)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(greater, >, BOOST_NUMERIC_FUNCTIONAL_DEDUCED)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(greater_equal, >=, BOOST_NUMERIC_FUNCTIONAL_DEDUCED)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(less, <, BOOST_NUMERIC_FUNCTIONAL_DEDUCED)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(less_equal, <=, BOOST_NUMERIC_FUNCTIONAL_DEDUCED)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(equal_to, ==, BOOST_NUMERIC_FUNCTIONAL_DEDUCED)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(not_equal_to, !=, BOOST_NUMERIC_FUNCTIONAL_DEDUCED)
+
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(assign, =, BOOST_NUMERIC_FUNCTIONAL_LEFT)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(plus_assign, +=, BOOST_NUMERIC_FUNCTIONAL_LEFT)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(minus_assign, -=, BOOST_NUMERIC_FUNCTIONAL_LEFT)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(multiplies_assign, *=, BOOST_NUMERIC_FUNCTIONAL_LEFT)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(divides_assign, /=, BOOST_NUMERIC_FUNCTIONAL_LEFT)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(modulus_assign, %=, BOOST_NUMERIC_FUNCTIONAL_LEFT)
+
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP(unary_plus, +)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP(unary_minus, -)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP(complement, ~)
+    BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP(logical_not, !)
+
+#undef BOOST_NUMERIC_FUNCTIONAL_LEFT
+#undef BOOST_NUMERIC_FUNCTIONAL_DEDUCED
+#undef BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP
+#undef BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP
+
+    namespace functional
+    {
+        template<typename Left, typename Right, typename EnableIf>
+        struct min_assign_base
+          : std::binary_function<Left, Right, void>
+        {
+            void operator ()(Left &left, Right &right) const
+            {
+                if(numeric::less(right, left))
+                {
+                    left = right;
+                }
+            }
+        };
+
+        template<typename Left, typename Right, typename EnableIf>
+        struct max_assign_base
+          : std::binary_function<Left, Right, void>
+        {
+            void operator ()(Left &left, Right &right) const
+            {
+                if(numeric::greater(right, left))
+                {
+                    left = right;
+                }
+            }
+        };
+
+        template<typename Left, typename Right, typename EnableIf>
+        struct average_base
+          : functional::divides<Left, Right>
+        {};
+
+        // partial specialization that promotes the arguments to double for
+        // integral division.
+        template<typename Left, typename Right>
+        struct average_base<Left, Right, typename enable_if<are_integral<Left, Right> >::type>
+          : functional::divides<double const, double const>
+        {};
+
+        template<typename To, typename From, typename EnableIf>
+        struct promote_base
+          : std::unary_function<From, To>
+        {
+            To operator ()(From &from) const
+            {
+                return from;
+            }
+        };
+
+        template<typename ToFrom>
+        struct promote_base<ToFrom, ToFrom, void>
+          : std::unary_function<ToFrom, ToFrom>
+        {
+            ToFrom &operator ()(ToFrom &tofrom)
+            {
+                return tofrom;
+            }
+        };
+
+        template<typename Arg, typename EnableIf>
+        struct as_min_base
+          : std::unary_function<Arg, typename remove_const<Arg>::type>
+        {
+            typename remove_const<Arg>::type operator ()(Arg &) const
+            {
+                return (std::numeric_limits<typename remove_const<Arg>::type>::min)();
+            }
+        };
+
+        template<typename Arg>
+        struct as_min_base<Arg, typename enable_if<is_floating_point<Arg> >::type>
+          : std::unary_function<Arg, typename remove_const<Arg>::type>
+        {
+            typename remove_const<Arg>::type operator ()(Arg &) const
+            {
+                return -(std::numeric_limits<typename remove_const<Arg>::type>::max)();
+            }
+        };
+
+        template<typename Arg, typename EnableIf>
+        struct as_max_base
+          : std::unary_function<Arg, typename remove_const<Arg>::type>
+        {
+            typename remove_const<Arg>::type operator ()(Arg &) const
+            {
+                return (std::numeric_limits<typename remove_const<Arg>::type>::max)();
+            }
+        };
+
+        template<typename Arg, typename EnableIf>
+        struct as_zero_base
+          : std::unary_function<Arg, typename remove_const<Arg>::type>
+        {
+            typename remove_const<Arg>::type operator ()(Arg &) const
+            {
+                return numeric::zero<typename remove_const<Arg>::type>::value;
+            }
+        };
+
+        template<typename Arg, typename EnableIf>
+        struct as_one_base
+          : std::unary_function<Arg, typename remove_const<Arg>::type>
+        {
+            typename remove_const<Arg>::type operator ()(Arg &) const
+            {
+                return numeric::one<typename remove_const<Arg>::type>::value;
+            }
+        };
+
+        template<typename To, typename From, typename ToTag, typename FromTag>
+        struct promote
+          : promote_base<To, From, void>
+        {};
+
+        template<typename Left, typename Right, typename LeftTag, typename RightTag>
+        struct min_assign
+          : min_assign_base<Left, Right, void>
+        {};
+
+        template<typename Left, typename Right, typename LeftTag, typename RightTag>
+        struct max_assign
+          : max_assign_base<Left, Right, void>
+        {};
+
+        template<typename Left, typename Right, typename LeftTag, typename RightTag>
+        struct average
+          : average_base<Left, Right, void>
+        {};
+
+        template<typename Arg, typename Tag>
+        struct as_min
+          : as_min_base<Arg, void>
+        {};
+
+        template<typename Arg, typename Tag>
+        struct as_max
+          : as_max_base<Arg, void>
+        {};
+
+        template<typename Arg, typename Tag>
+        struct as_zero
+          : as_zero_base<Arg, void>
+        {};
+
+        template<typename Arg, typename Tag>
+        struct as_one
+          : as_one_base<Arg, void>
+        {};
+    }
+
+    namespace op
+    {
+        template<typename To>
+        struct promote
+          : boost::detail::function1<functional::promote<To, _, typename functional::tag<To>::type, functional::tag<_> > >
+        {};
+
+        struct min_assign
+          : boost::detail::function2<functional::min_assign<_1, _2, functional::tag<_1>, functional::tag<_2> > >
+        {};
+
+        struct max_assign
+          : boost::detail::function2<functional::max_assign<_1, _2, functional::tag<_1>, functional::tag<_2> > >
+        {};
+
+        struct average
+          : boost::detail::function2<functional::average<_1, _2, functional::tag<_1>, functional::tag<_2> > >
+        {};
+
+        struct as_min
+          : boost::detail::function1<functional::as_min<_, functional::tag<_> > >
+        {};
+
+        struct as_max
+          : boost::detail::function1<functional::as_max<_, functional::tag<_> > >
+        {};
+
+        struct as_zero
+          : boost::detail::function1<functional::as_zero<_, functional::tag<_> > >
+        {};
+
+        struct as_one
+          : boost::detail::function1<functional::as_one<_, functional::tag<_> > >
+        {};
+    }
+
+    namespace
+    {
+        op::min_assign const &min_assign = boost::detail::pod_singleton<op::min_assign>::instance;
+        op::max_assign const &max_assign = boost::detail::pod_singleton<op::max_assign>::instance;
+        op::average const &average = boost::detail::pod_singleton<op::average>::instance;
+        op::as_min const &as_min = boost::detail::pod_singleton<op::as_min>::instance;
+        op::as_max const &as_max = boost::detail::pod_singleton<op::as_max>::instance;
+        op::as_zero const &as_zero = boost::detail::pod_singleton<op::as_zero>::instance;
+        op::as_one const &as_one = boost::detail::pod_singleton<op::as_one>::instance;
+    }
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // promote
+    template<typename To, typename From>
+    typename lazy_disable_if<is_const<From>, mpl::if_<is_same<To, From>, To &, To> >::type
+    promote(From &from)
+    {
+        return functional::promote<To, From>()(from);
+    }
+
+    template<typename To, typename From>
+    typename mpl::if_<is_same<To const, From const>, To const &, To const>::type
+    promote(From const &from)
+    {
+        return functional::promote<To const, From const>()(from);
+    }
+
+    template<typename T>
+    struct empty
+    {
+        typedef empty type;
+        typedef T value_type;
+        static T const value;
+
+        operator T const & () const
+        {
+            return empty::value;
+        }
+    };
+
+    template<typename T>
+    T const empty<T>::value = T();
+
+    template<typename T>
+    struct one
+    {
+        typedef one type;
+        typedef T value_type;
+        static T const value;
+
+        operator T const & () const
+        {
+            return one::value;
+        }
+    };
+
+    template<typename T>
+    T const one<T>::value = T(1);
+
+    template<typename T>
+    struct zero
+    {
+        typedef zero type;
+        typedef T value_type;
+        static T const value;
+
+        operator T const & () const
+        {
+            return zero::value;
+        }
+    };
+
+    template<typename T>
+    T const zero<T>::value = T();
+
+    template<typename T>
+    struct one_or_empty
+      : mpl::if_<is_empty<T>, empty<T>, one<T> >::type
+    {};
+
+    template<typename T>
+    struct zero_or_empty
+      : mpl::if_<is_empty<T>, empty<T>, zero<T> >::type
+    {};
+
+}} // namespace boost::numeric
+
+#endif

Added: trunk/boost/accumulators/numeric/functional/complex.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/numeric/functional/complex.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,82 @@
+///////////////////////////////////////////////////////////////////////////////
+/// \file complex.hpp
+///
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_NUMERIC_FUNCTIONAL_COMPLEX_HPP_EAN_01_17_2006
+#define BOOST_NUMERIC_FUNCTIONAL_COMPLEX_HPP_EAN_01_17_2006
+
+#ifdef BOOST_NUMERIC_FUNCTIONAL_HPP_INCLUDED
+# error Include this file before boost/accumulators/numeric/functional.hpp
+#endif
+
+#include <complex>
+#include <boost/mpl/or.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/utility/enable_if.hpp>
+#include <boost/typeof/std/complex.hpp>
+#include <boost/accumulators/numeric/functional_fwd.hpp>
+
+namespace boost { namespace numeric { namespace operators
+{
+    // So that the stats compile when Sample type is std::complex
+    template<typename T, typename U>
+    typename
+        disable_if<
+            mpl::or_<is_same<T, U>, is_same<std::complex<T>, U> >
+          , std::complex<T>
+        >::type
+    operator *(std::complex<T> ri, U const &u)
+    {
+        // BUGBUG promote result to typeof(T()*u) ?
+        return ri *= static_cast<T>(u);
+    }
+
+    template<typename T, typename U>
+    typename
+        disable_if<
+            mpl::or_<is_same<T, U>, is_same<std::complex<T>, U> >
+          , std::complex<T>
+        >::type
+    operator /(std::complex<T> ri, U const &u)
+    {
+        // BUGBUG promote result to typeof(T()*u) ?
+        return ri /= static_cast<T>(u);
+    }
+
+}}} // namespace boost::numeric::operators
+
+namespace boost { namespace numeric
+{
+    namespace detail
+    {
+        template<typename T>
+        struct one_complex
+        {
+            static std::complex<T> const value;
+        };
+
+        template<typename T>
+        std::complex<T> const one_complex<T>::value
+          = std::complex<T>(numeric::one<T>::value, numeric::one<T>::value);
+    }
+
+    /// INTERNAL ONLY
+    ///
+    template<typename T>
+    struct one<std::complex<T> >
+      : detail::one_complex<T>
+    {
+        typedef one type;
+        typedef std::complex<T> value_type;
+        operator value_type const & () const
+        {
+            return detail::one_complex<T>::value;
+        }
+    };
+
+}} // namespace boost::numeric
+
+#endif

Added: trunk/boost/accumulators/numeric/functional/valarray.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/numeric/functional/valarray.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,351 @@
+///////////////////////////////////////////////////////////////////////////////
+/// \file valarray.hpp
+///
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_NUMERIC_FUNCTIONAL_VALARRAY_HPP_EAN_12_12_2005
+#define BOOST_NUMERIC_FUNCTIONAL_VALARRAY_HPP_EAN_12_12_2005
+
+#ifdef BOOST_NUMERIC_FUNCTIONAL_HPP_INCLUDED
+# error Include this file before boost/accumulators/numeric/functional.hpp
+#endif
+
+#include <valarray>
+#include <functional>
+#include <boost/assert.hpp>
+#include <boost/mpl/and.hpp>
+#include <boost/mpl/not.hpp>
+#include <boost/mpl/assert.hpp>
+#include <boost/utility/enable_if.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/type_traits/is_scalar.hpp>
+#include <boost/type_traits/remove_const.hpp>
+#include <boost/typeof/std/valarray.hpp>
+#include <boost/accumulators/numeric/functional_fwd.hpp>
+
+namespace boost { namespace numeric
+{
+    namespace operators
+    {
+        ///////////////////////////////////////////////////////////////////////////////
+        // Handle valarray<Left> / Right where Right is a scalar and Right != Left.
+        template<typename Left, typename Right>
+        typename enable_if<
+            mpl::and_<is_scalar<Right>, mpl::not_<is_same<Left, Right> > >
+          , std::valarray<typename functional::divides<Left, Right>::result_type>
+        >::type
+        operator /(std::valarray<Left> const &left, Right const &right)
+        {
+            typedef typename functional::divides<Left, Right>::result_type value_type;
+            std::valarray<value_type> result(left.size());
+            for(std::size_t i = 0, size = result.size(); i != size; ++i)
+            {
+                result[i] = numeric::divides(left[i], right);
+            }
+            return result;
+        }
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // Handle valarray<Left> * Right where Right is a scalar and Right != Left.
+        template<typename Left, typename Right>
+        typename enable_if<
+            mpl::and_<is_scalar<Right>, mpl::not_<is_same<Left, Right> > >
+          , std::valarray<typename functional::multiplies<Left, Right>::result_type>
+        >::type
+        operator *(std::valarray<Left> const &left, Right const &right)
+        {
+            typedef typename functional::multiplies<Left, Right>::result_type value_type;
+            std::valarray<value_type> result(left.size());
+            for(std::size_t i = 0, size = result.size(); i != size; ++i)
+            {
+                result[i] = numeric::multiplies(left[i], right);
+            }
+            return result;
+        }
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // Handle valarray<Left> + valarray<Right> where Right != Left.
+        template<typename Left, typename Right>
+        typename disable_if<
+            is_same<Left, Right>
+          , std::valarray<typename functional::plus<Left, Right>::result_type>
+        >::type
+        operator +(std::valarray<Left> const &left, std::valarray<Right> const &right)
+        {
+            typedef typename functional::plus<Left, Right>::result_type value_type;
+            std::valarray<value_type> result(left.size());
+            for(std::size_t i = 0, size = result.size(); i != size; ++i)
+            {
+                result[i] = numeric::plus(left[i], right[i]);
+            }
+            return result;
+        }
+    }
+
+    namespace functional
+    {
+        struct std_valarray_tag;
+
+        template<typename T>
+        struct tag<std::valarray<T> >
+        {
+            typedef std_valarray_tag type;
+        };
+
+    #ifdef __GLIBCXX__
+        template<typename T, typename U>
+        struct tag<std::_Expr<T, U> >
+        {
+            typedef std_valarray_tag type;
+        };
+    #endif
+
+        /// INTERNAL ONLY
+        ///
+        // This is necessary because the GCC stdlib uses expression templates, and
+        // typeof(som-valarray-expression) is not an instance of std::valarray
+    #define BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP(Name, Op)                   \
+        template<typename Left, typename Right>                                         \
+        struct Name<Left, Right, std_valarray_tag, std_valarray_tag>                    \
+          : std::binary_function<                                                       \
+                Left                                                                    \
+              , Right                                                                   \
+              , std::valarray<                                                          \
+                    typename Name<                                                      \
+                        typename Left::value_type                                       \
+                      , typename Right::value_type                                      \
+                    >::result_type                                                      \
+                >                                                                       \
+            >                                                                           \
+        {                                                                               \
+            typedef typename Left::value_type left_value_type;                          \
+            typedef typename Right::value_type right_value_type;                        \
+            typedef                                                                     \
+                std::valarray<                                                          \
+                    typename Name<left_value_type, right_value_type>::result_type       \
+                >                                                                       \
+            result_type;                                                                \
+            result_type                                                                 \
+            operator ()(Left &left, Right &right) const                                 \
+            {                                                                           \
+                return numeric::promote<std::valarray<left_value_type> >(left)          \
+                    Op numeric::promote<std::valarray<right_value_type> >(right);       \
+            }                                                                           \
+        };                                                                              \
+        template<typename Left, typename Right>                                         \
+        struct Name<Left, Right, std_valarray_tag, void>                                \
+          : std::binary_function<                                                       \
+                Left                                                                    \
+              , Right                                                                   \
+              , std::valarray<                                                          \
+                    typename Name<typename Left::value_type, Right>::result_type        \
+                >                                                                       \
+            >                                                                           \
+        {                                                                               \
+            typedef typename Left::value_type left_value_type;                          \
+            typedef                                                                     \
+                std::valarray<                                                          \
+                    typename Name<left_value_type, Right>::result_type                  \
+                >                                                                       \
+            result_type;                                                                \
+            result_type                                                                 \
+            operator ()(Left &left, Right &right) const                                 \
+            {                                                                           \
+                return numeric::promote<std::valarray<left_value_type> >(left) Op right;\
+            }                                                                           \
+        };                                                                              \
+        template<typename Left, typename Right>                                         \
+        struct Name<Left, Right, void, std_valarray_tag>                                \
+          : std::binary_function<                                                       \
+                Left                                                                    \
+              , Right                                                                   \
+              , std::valarray<                                                          \
+                    typename Name<Left, typename Right::value_type>::result_type        \
+                >                                                                       \
+            >                                                                           \
+        {                                                                               \
+            typedef typename Right::value_type right_value_type;                        \
+            typedef                                                                     \
+                std::valarray<                                                          \
+                    typename Name<Left, right_value_type>::result_type                  \
+                >                                                                       \
+            result_type;                                                                \
+            result_type                                                                 \
+            operator ()(Left &left, Right &right) const                                 \
+            {                                                                           \
+                return left Op numeric::promote<std::valarray<right_value_type> >(right);\
+            }                                                                           \
+        };
+
+        BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP(plus, +)
+        BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP(minus, -)
+        BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP(multiplies, *)
+        BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP(divides, /)
+        BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP(modulus, %)
+
+    #undef BOOST_NUMERIC_FUNCTIONAL_DEFINE_VALARRAY_BIN_OP
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // element-wise min of std::valarray
+        template<typename Left, typename Right>
+        struct min_assign<Left, Right, std_valarray_tag, std_valarray_tag>
+          : std::binary_function<Left, Right, void>
+        {
+            void operator ()(Left &left, Right &right) const
+            {
+                BOOST_ASSERT(left.size() == right.size());
+                for(std::size_t i = 0, size = left.size(); i != size; ++i)
+                {
+                    if(numeric::less(right[i], left[i]))
+                    {
+                        left[i] = right[i];
+                    }
+                }
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // element-wise max of std::valarray
+        template<typename Left, typename Right>
+        struct max_assign<Left, Right, std_valarray_tag, std_valarray_tag>
+          : std::binary_function<Left, Right, void>
+        {
+            void operator ()(Left &left, Right &right) const
+            {
+                BOOST_ASSERT(left.size() == right.size());
+                for(std::size_t i = 0, size = left.size(); i != size; ++i)
+                {
+                    if(numeric::greater(right[i], left[i]))
+                    {
+                        left[i] = right[i];
+                    }
+                }
+            }
+        };
+
+        // partial specialization of numeric::average<> for std::valarray.
+        template<typename Left, typename Right, typename RightTag>
+        struct average<Left, Right, std_valarray_tag, RightTag>
+          : mpl::if_<
+                are_integral<typename Left::value_type, Right>
+              , divides<Left, double const>
+              , divides<Left, Right>
+            >::type
+        {};
+
+        // promote
+        template<typename To, typename From>
+        struct promote<To, From, std_valarray_tag, std_valarray_tag>
+          : std::unary_function<From, To>
+        {
+            To operator ()(From &arr) const
+            {
+                typename remove_const<To>::type res(arr.size());
+                for(std::size_t i = 0, size = arr.size(); i != size; ++i)
+                {
+                    res[i] = numeric::promote<typename To::value_type>(arr[i]);
+                }
+                return res;
+            }
+        };
+
+        template<typename ToFrom>
+        struct promote<ToFrom, ToFrom, std_valarray_tag, std_valarray_tag>
+          : std::unary_function<ToFrom, ToFrom>
+        {
+            ToFrom &operator ()(ToFrom &tofrom) const
+            {
+                return tofrom;
+            }
+        };
+
+        // for "promoting" a std::valarray<bool> to a bool, useful for
+        // comparing 2 valarrays for equality:
+        //   if(numeric::promote<bool>(a == b))
+        template<typename From>
+        struct promote<bool, From, void, std_valarray_tag>
+          : std::unary_function<From, bool>
+        {
+            bool operator ()(From &arr) const
+            {
+                BOOST_MPL_ASSERT((is_same<bool, typename From::value_type>));
+                for(std::size_t i = 0, size = arr.size(); i != size; ++i)
+                {
+                    if(!arr[i])
+                    {
+                        return false;
+                    }
+                }
+                return true;
+            }
+        };
+
+        template<typename From>
+        struct promote<bool const, From, void, std_valarray_tag>
+          : promote<bool, From, void, std_valarray_tag>
+        {};
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // functional::as_min
+        template<typename T>
+        struct as_min<T, std_valarray_tag>
+            : std::unary_function<T, typename remove_const<T>::type>
+        {
+            typename remove_const<T>::type operator ()(T &arr) const
+            {
+                return 0 == arr.size()
+                  ? T()
+                  : T(numeric::as_min(arr[0]), arr.size());
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // functional::as_max
+        template<typename T>
+        struct as_max<T, std_valarray_tag>
+          : std::unary_function<T, typename remove_const<T>::type>
+        {
+            typename remove_const<T>::type operator ()(T &arr) const
+            {
+                return 0 == arr.size()
+                  ? T()
+                  : T(numeric::as_max(arr[0]), arr.size());
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // functional::as_zero
+        template<typename T>
+        struct as_zero<T, std_valarray_tag>
+          : std::unary_function<T, typename remove_const<T>::type>
+        {
+            typename remove_const<T>::type operator ()(T &arr) const
+            {
+                return 0 == arr.size()
+                  ? T()
+                  : T(numeric::as_zero(arr[0]), arr.size());
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // functional::as_one
+        template<typename T>
+        struct as_one<T, std_valarray_tag>
+          : std::unary_function<T, typename remove_const<T>::type>
+        {
+            typename remove_const<T>::type operator ()(T &arr) const
+            {
+                return 0 == arr.size()
+                  ? T()
+                  : T(numeric::as_one(arr[0]), arr.size());
+            }
+        };
+
+    } // namespace functional
+
+}} // namespace boost::numeric
+
+#endif
+

Added: trunk/boost/accumulators/numeric/functional/vector.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/numeric/functional/vector.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,320 @@
+///////////////////////////////////////////////////////////////////////////////
+/// \file vector.hpp
+///
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_NUMERIC_FUNCTIONAL_VECTOR_HPP_EAN_12_12_2005
+#define BOOST_NUMERIC_FUNCTIONAL_VECTOR_HPP_EAN_12_12_2005
+
+#ifdef BOOST_NUMERIC_FUNCTIONAL_HPP_INCLUDED
+# error Include this file before boost/accumulators/numeric/functional.hpp
+#endif
+
+#include <vector>
+#include <functional>
+#include <boost/assert.hpp>
+#include <boost/mpl/and.hpp>
+#include <boost/mpl/not.hpp>
+#include <boost/utility/enable_if.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/type_traits/is_scalar.hpp>
+#include <boost/type_traits/remove_const.hpp>
+#include <boost/typeof/std/vector.hpp>
+#include <boost/accumulators/numeric/functional_fwd.hpp>
+
+namespace boost { namespace numeric
+{
+    namespace operators
+    {
+        ///////////////////////////////////////////////////////////////////////////////
+        // Handle vector<Left> / Right where Right is a scalar.
+        template<typename Left, typename Right>
+        typename enable_if<
+            is_scalar<Right>
+          , std::vector<typename functional::divides<Left, Right>::result_type>
+        >::type
+        operator /(std::vector<Left> const &left, Right const &right)
+        {
+            typedef typename functional::divides<Left, Right>::result_type value_type;
+            std::vector<value_type> result(left.size());
+            for(std::size_t i = 0, size = result.size(); i != size; ++i)
+            {
+                result[i] = numeric::divides(left[i], right);
+            }
+            return result;
+        }
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // Handle vector<Left> / vector<Right>.
+        template<typename Left, typename Right>
+        std::vector<typename functional::divides<Left, Right>::result_type>
+        operator /(std::vector<Left> const &left, std::vector<Right> const &right)
+        {
+            typedef typename functional::divides<Left, Right>::result_type value_type;
+            std::vector<value_type> result(left.size());
+            for(std::size_t i = 0, size = result.size(); i != size; ++i)
+            {
+                result[i] = numeric::divides(left[i], right[i]);
+            }
+            return result;
+        }
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // Handle vector<Left> * Right where Right is a scalar.
+        template<typename Left, typename Right>
+        typename enable_if<
+            is_scalar<Right>
+          , std::vector<typename functional::multiplies<Left, Right>::result_type>
+        >::type
+        operator *(std::vector<Left> const &left, Right const &right)
+        {
+            typedef typename functional::multiplies<Left, Right>::result_type value_type;
+            std::vector<value_type> result(left.size());
+            for(std::size_t i = 0, size = result.size(); i != size; ++i)
+            {
+                result[i] = numeric::multiplies(left[i], right);
+            }
+            return result;
+        }
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // Handle Left * vector<Right> where Left is a scalar.
+        template<typename Left, typename Right>
+        typename enable_if<
+            is_scalar<Left>
+          , std::vector<typename functional::multiplies<Left, Right>::result_type>
+        >::type
+        operator *(Left const &left, std::vector<Right> const &right)
+        {
+            typedef typename functional::multiplies<Left, Right>::result_type value_type;
+            std::vector<value_type> result(right.size());
+            for(std::size_t i = 0, size = result.size(); i != size; ++i)
+            {
+                result[i] = numeric::multiplies(left, right[i]);
+            }
+            return result;
+        }
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // Handle vector<Left> * vector<Right>
+        template<typename Left, typename Right>
+        std::vector<typename functional::multiplies<Left, Right>::result_type>
+        operator *(std::vector<Left> const &left, std::vector<Right> const &right)
+        {
+            typedef typename functional::multiplies<Left, Right>::result_type value_type;
+            std::vector<value_type> result(left.size());
+            for(std::size_t i = 0, size = result.size(); i != size; ++i)
+            {
+                result[i] = numeric::multiplies(left[i], right[i]);
+            }
+            return result;
+        }
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // Handle vector<Left> + vector<Right>
+        template<typename Left, typename Right>
+        std::vector<typename functional::plus<Left, Right>::result_type>
+        operator +(std::vector<Left> const &left, std::vector<Right> const &right)
+        {
+            typedef typename functional::plus<Left, Right>::result_type value_type;
+            std::vector<value_type> result(left.size());
+            for(std::size_t i = 0, size = result.size(); i != size; ++i)
+            {
+                result[i] = numeric::plus(left[i], right[i]);
+            }
+            return result;
+        }
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // Handle vector<Left> - vector<Right>
+        template<typename Left, typename Right>
+        std::vector<typename functional::minus<Left, Right>::result_type>
+        operator -(std::vector<Left> const &left, std::vector<Right> const &right)
+        {
+            typedef typename functional::minus<Left, Right>::result_type value_type;
+            std::vector<value_type> result(left.size());
+            for(std::size_t i = 0, size = result.size(); i != size; ++i)
+            {
+                result[i] = numeric::minus(left[i], right[i]);
+            }
+            return result;
+        }
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // Handle vector<Left> += vector<Left>
+        template<typename Left>
+        std::vector<Left> &
+        operator +=(std::vector<Left> &left, std::vector<Left> const &right)
+        {
+            BOOST_ASSERT(left.size() == right.size());
+            for(std::size_t i = 0, size = left.size(); i != size; ++i)
+            {
+                numeric::plus_assign(left[i], right[i]);
+            }
+            return left;
+        }
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // Handle -vector<Arg>
+        template<typename Arg>
+        std::vector<typename functional::unary_minus<Arg>::result_type>
+        operator -(std::vector<Arg> const &arg)
+        {
+            typedef typename functional::unary_minus<Arg>::result_type value_type;
+            std::vector<value_type> result(arg.size());
+            for(std::size_t i = 0, size = result.size(); i != size; ++i)
+            {
+                result[i] = numeric::unary_minus(arg[i]);
+            }
+            return result;
+        }
+    }
+
+    namespace functional
+    {
+        struct std_vector_tag;
+
+        template<typename T, typename Al>
+        struct tag<std::vector<T, Al> >
+        {
+            typedef std_vector_tag type;
+        };
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // element-wise min of std::vector
+        template<typename Left, typename Right>
+        struct min_assign<Left, Right, std_vector_tag, std_vector_tag>
+          : std::binary_function<Left, Right, void>
+        {
+            void operator ()(Left &left, Right &right) const
+            {
+                BOOST_ASSERT(left.size() == right.size());
+                for(std::size_t i = 0, size = left.size(); i != size; ++i)
+                {
+                    if(numeric::less(right[i], left[i]))
+                    {
+                        left[i] = right[i];
+                    }
+                }
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // element-wise max of std::vector
+        template<typename Left, typename Right>
+        struct max_assign<Left, Right, std_vector_tag, std_vector_tag>
+          : std::binary_function<Left, Right, void>
+        {
+            void operator ()(Left &left, Right &right) const
+            {
+                BOOST_ASSERT(left.size() == right.size());
+                for(std::size_t i = 0, size = left.size(); i != size; ++i)
+                {
+                    if(numeric::greater(right[i], left[i]))
+                    {
+                        left[i] = right[i];
+                    }
+                }
+            }
+        };
+
+        // partial specialization for std::vector.
+        template<typename Left, typename Right>
+        struct average<Left, Right, std_vector_tag, void>
+          : mpl::if_<
+                are_integral<typename Left::value_type, Right>
+              , divides<Left, double const>
+              , divides<Left, Right>
+            >::type
+        {};
+
+        // promote
+        template<typename To, typename From>
+        struct promote<To, From, std_vector_tag, std_vector_tag>
+          : std::unary_function<From, To>
+        {
+            To operator ()(From &arr) const
+            {
+                typename remove_const<To>::type res(arr.size());
+                for(std::size_t i = 0, size = arr.size(); i != size; ++i)
+                {
+                    res[i] = numeric::promote<typename To::value_type>(arr[i]);
+                }
+                return res;
+            }
+        };
+
+        template<typename ToFrom>
+        struct promote<ToFrom, ToFrom, std_vector_tag, std_vector_tag>
+          : std::unary_function<ToFrom, ToFrom>
+        {
+            ToFrom &operator ()(ToFrom &tofrom) const
+            {
+                return tofrom;
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // functional::as_min
+        template<typename T>
+        struct as_min<T, std_vector_tag>
+          : std::unary_function<T, typename remove_const<T>::type>
+        {
+            typename remove_const<T>::type operator ()(T &arr) const
+            {
+                return 0 == arr.size()
+                  ? T()
+                  : T(arr.size(), numeric::as_min(arr[0]));
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // functional::as_max
+        template<typename T>
+        struct as_max<T, std_vector_tag>
+          : std::unary_function<T, typename remove_const<T>::type>
+        {
+            typename remove_const<T>::type operator ()(T &arr) const
+            {
+                return 0 == arr.size()
+                  ? T()
+                  : T(arr.size(), numeric::as_max(arr[0]));
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // functional::as_zero
+        template<typename T>
+        struct as_zero<T, std_vector_tag>
+          : std::unary_function<T, typename remove_const<T>::type>
+        {
+            typename remove_const<T>::type operator ()(T &arr) const
+            {
+                return 0 == arr.size()
+                  ? T()
+                  : T(arr.size(), numeric::as_zero(arr[0]));
+            }
+        };
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // functional::as_one
+        template<typename T>
+        struct as_one<T, std_vector_tag>
+          : std::unary_function<T, typename remove_const<T>::type>
+        {
+            typename remove_const<T>::type operator ()(T &arr) const
+            {
+                return 0 == arr.size()
+                  ? T()
+                  : T(arr.size(), numeric::as_one(arr[0]));
+            }
+        };
+
+    } // namespace functional
+
+}} // namespace boost::numeric
+
+#endif
+

Added: trunk/boost/accumulators/numeric/functional_fwd.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/numeric/functional_fwd.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,221 @@
+///////////////////////////////////////////////////////////////////////////////
+/// \file functional_fwd.hpp
+///
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_NUMERIC_FUNCTIONAL_FWD_HPP_EAN_08_12_2005
+#define BOOST_NUMERIC_FUNCTIONAL_FWD_HPP_EAN_08_12_2005
+
+#include <boost/mpl/if.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/utility/enable_if.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/type_traits/is_const.hpp>
+
+namespace boost { namespace numeric
+{
+    // For using directives -- this namespace may be re-opened elsewhere
+    namespace operators
+    {}
+
+    namespace op
+    {
+        using mpl::_;
+        using mpl::_1;
+        using mpl::_2;
+    }
+
+    namespace functional
+    {
+        using namespace operators;
+
+        template<typename T>
+        struct tag
+        {
+            typedef void type;
+        };
+
+        template<typename T>
+        struct tag<T const>
+          : tag<T>
+        {};
+
+        template<typename T>
+        struct tag<T volatile>
+          : tag<T>
+        {};
+
+        template<typename T>
+        struct tag<T const volatile>
+          : tag<T>
+        {};
+
+        template<typename T>
+        struct static_;
+
+        template<typename A0, typename A1>
+        struct are_integral;
+    }
+
+    /// INTERNAL ONLY
+    ///
+#define BOOST_NUMERIC_FUNCTIONAL_DECLARE_UNARY_OP(Name, Op)                                     \
+    namespace functional                                                                        \
+    {                                                                                           \
+        template<typename Arg, typename EnableIf = void>                                        \
+        struct Name ## _base;                                                                   \
+        template<typename Arg, typename ArgTag = typename tag<Arg>::type>                       \
+        struct Name;                                                                            \
+    }                                                                                           \
+    namespace op                                                                                \
+    {                                                                                           \
+        struct Name;                                                                            \
+    }                                                                                           \
+    namespace                                                                                   \
+    {                                                                                           \
+        extern op::Name const &Name;                                                            \
+    }
+
+    /// INTERNAL ONLY
+    ///
+#define BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(Name)                                        \
+    namespace functional                                                                        \
+    {                                                                                           \
+        template<typename Left, typename Right, typename EnableIf = void>                       \
+        struct result_of_ ## Name;                                                              \
+        template<typename Left, typename Right, typename EnableIf = void>                       \
+        struct Name ## _base;                                                                   \
+        template<                                                                               \
+            typename Left                                                                       \
+          , typename Right                                                                      \
+          , typename LeftTag = typename tag<Left>::type                                         \
+          , typename RightTag = typename tag<Right>::type                                       \
+        >                                                                                       \
+        struct Name;                                                                            \
+    }                                                                                           \
+    namespace op                                                                                \
+    {                                                                                           \
+        struct Name;                                                                            \
+    }                                                                                           \
+    namespace                                                                                   \
+    {                                                                                           \
+        extern op::Name const &Name;                                                            \
+    }
+
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(plus)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(minus)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(multiplies)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(divides)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(modulus)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(greater)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(greater_equal)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(less)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(less_equal)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(equal_to)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(not_equal_to)
+
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(assign)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(plus_assign)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(minus_assign)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(multiplies_assign)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(divides_assign)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP(modulus_assign)
+
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_UNARY_OP(unary_plus, +)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_UNARY_OP(unary_minus, -)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_UNARY_OP(complement, ~)
+    BOOST_NUMERIC_FUNCTIONAL_DECLARE_UNARY_OP(logical_not, !)
+
+#undef BOOST_NUMERIC_FUNCTIONAL_DECLARE_UNARY_OP
+#undef BOOST_NUMERIC_FUNCTIONAL_DECLARE_BINARY_OP
+
+
+    namespace functional
+    {
+        template<typename To, typename From, typename EnableIf = void>
+        struct promote_base;
+        template<typename Left, typename Right, typename EnableIf = void>
+        struct min_assign_base;
+        template<typename Left, typename Right, typename EnableIf = void>
+        struct max_assign_base;
+        template<typename Left, typename Right, typename EnableIf = void>
+        struct average_base;
+        template<typename Arg, typename EnableIf = void>
+        struct as_min_base;
+        template<typename Arg, typename EnableIf = void>
+        struct as_max_base;
+        template<typename Arg, typename EnableIf = void>
+        struct as_zero_base;
+        template<typename Arg, typename EnableIf = void>
+        struct as_one_base;
+
+        template<typename To, typename From, typename ToTag = typename tag<To>::type, typename FromTag = typename tag<From>::type>
+        struct promote;
+        template<typename Left, typename Right, typename LeftTag = typename tag<Left>::type, typename RightTag = typename tag<Right>::type>
+        struct min_assign;
+        template<typename Left, typename Right, typename LeftTag = typename tag<Left>::type, typename RightTag = typename tag<Right>::type>
+        struct max_assign;
+        template<typename Left, typename Right, typename LeftTag = typename tag<Left>::type, typename RightTag = typename tag<Right>::type>
+        struct average;
+        template<typename Arg, typename Tag = typename tag<Arg>::type>
+        struct as_min;
+        template<typename Arg, typename Tag = typename tag<Arg>::type>
+        struct as_max;
+        template<typename Arg, typename Tag = typename tag<Arg>::type>
+        struct as_zero;
+        template<typename Arg, typename Tag = typename tag<Arg>::type>
+        struct as_one;
+    }
+
+    namespace op
+    {
+        template<typename To>
+        struct promote;
+        struct min_assign;
+        struct max_assign;
+        struct average;
+        struct as_min;
+        struct as_max;
+        struct as_zero;
+        struct as_one;
+    }
+
+    namespace
+    {
+        extern op::min_assign const &min_assign;
+        extern op::max_assign const &max_assign;
+        extern op::average const &average;
+        extern op::as_min const &as_min;
+        extern op::as_max const &as_max;
+        extern op::as_zero const &as_zero;
+        extern op::as_one const &as_one;
+    }
+
+    template<typename To, typename From>
+    typename lazy_disable_if<is_const<From>, mpl::if_<is_same<To, From>, To &, To> >::type
+    promote(From &from);
+
+    template<typename To, typename From>
+    typename mpl::if_<is_same<To const, From const>, To const &, To const>::type
+    promote(From const &from);
+
+    template<typename T>
+    struct empty;
+
+    template<typename T>
+    struct one;
+
+    template<typename T>
+    struct zero;
+
+    template<typename T>
+    struct one_or_empty;
+
+    template<typename T>
+    struct zero_or_empty;
+
+}} // namespace boost::numeric
+
+#endif

Added: trunk/boost/accumulators/statistics.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,59 @@
+///////////////////////////////////////////////////////////////////////////////
+/// \file statistics.hpp
+/// Includes all of the Statistical Accumulators Library
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_HPP_EAN_01_17_2006
+#define BOOST_ACCUMULATORS_STATISTICS_HPP_EAN_01_17_2006
+
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/covariance.hpp>
+#include <boost/accumulators/statistics/density.hpp>
+#include <boost/accumulators/statistics/error_of.hpp>
+#include <boost/accumulators/statistics/error_of_mean.hpp>
+#include <boost/accumulators/statistics/extended_p_square.hpp>
+#include <boost/accumulators/statistics/extended_p_square_quantile.hpp>
+#include <boost/accumulators/statistics/kurtosis.hpp>
+#include <boost/accumulators/statistics/max.hpp>
+#include <boost/accumulators/statistics/mean.hpp>
+#include <boost/accumulators/statistics/median.hpp>
+#include <boost/accumulators/statistics/min.hpp>
+#include <boost/accumulators/statistics/moment.hpp>
+#include <boost/accumulators/statistics/peaks_over_threshold.hpp>
+#include <boost/accumulators/statistics/pot_tail_mean.hpp>
+#include <boost/accumulators/statistics/pot_quantile.hpp>
+#include <boost/accumulators/statistics/p_square_cumulative_distribution.hpp>
+#include <boost/accumulators/statistics/p_square_quantile.hpp>
+#include <boost/accumulators/statistics/skewness.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/sum.hpp>
+#include <boost/accumulators/statistics/tail.hpp>
+#include <boost/accumulators/statistics/tail_quantile.hpp>
+#include <boost/accumulators/statistics/tail_mean.hpp>
+#include <boost/accumulators/statistics/tail_variate.hpp>
+#include <boost/accumulators/statistics/tail_variate_means.hpp>
+#include <boost/accumulators/statistics/variance.hpp>
+#include <boost/accumulators/statistics/weighted_covariance.hpp>
+#include <boost/accumulators/statistics/weighted_density.hpp>
+#include <boost/accumulators/statistics/weighted_kurtosis.hpp>
+#include <boost/accumulators/statistics/weighted_extended_p_square.hpp>
+#include <boost/accumulators/statistics/weighted_mean.hpp>
+#include <boost/accumulators/statistics/weighted_median.hpp>
+#include <boost/accumulators/statistics/weighted_moment.hpp>
+#include <boost/accumulators/statistics/weighted_peaks_over_threshold.hpp>
+#include <boost/accumulators/statistics/weighted_p_square_cumulative_distribution.hpp>
+#include <boost/accumulators/statistics/weighted_p_square_quantile.hpp>
+#include <boost/accumulators/statistics/weighted_skewness.hpp>
+#include <boost/accumulators/statistics/weighted_sum.hpp>
+#include <boost/accumulators/statistics/weighted_tail_quantile.hpp>
+#include <boost/accumulators/statistics/weighted_tail_mean.hpp>
+#include <boost/accumulators/statistics/weighted_tail_variate_means.hpp>
+#include <boost/accumulators/statistics/weighted_variance.hpp>
+#include <boost/accumulators/statistics/with_error.hpp>
+#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
+#include <boost/accumulators/statistics/variates/covariate.hpp>
+
+#endif

Added: trunk/boost/accumulators/statistics/count.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/count.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,78 @@
+///////////////////////////////////////////////////////////////////////////////
+// count.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_COUNT_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_COUNT_HPP_EAN_28_10_2005
+
+#include <boost/mpl/always.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // count_impl
+    struct count_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef std::size_t result_type;
+
+        count_impl(dont_care)
+          : cnt(0)
+        {
+        }
+
+        void operator ()(dont_care)
+        {
+            ++this->cnt;
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->cnt;
+        }
+
+    private:
+        std::size_t cnt;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::count
+//
+namespace tag
+{
+    struct count
+      : depends_on<>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef mpl::always<accumulators::impl::count_impl> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::count
+//
+namespace extract
+{
+    extractor<tag::count> const count = {};
+}
+
+using extract::count;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/covariance.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/covariance.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,219 @@
+///////////////////////////////////////////////////////////////////////////////
+// covariance.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_COVARIANCE_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_COVARIANCE_HPP_DE_01_01_2006
+
+#include <vector>
+#include <limits>
+#include <numeric>
+#include <functional>
+#include <complex>
+#include <boost/mpl/assert.hpp>
+#include <boost/mpl/bool.hpp>
+#include <boost/range.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/lambda/lambda.hpp>
+#include <boost/numeric/ublas/io.hpp>
+#include <boost/numeric/ublas/matrix.hpp>
+#include <boost/type_traits/is_scalar.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/mean.hpp>
+
+namespace boost { namespace numeric
+{
+    namespace functional
+    {
+        struct std_vector_tag;
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // functional::outer_product
+        template<typename Left, typename Right, typename EnableIf = void>
+        struct outer_product_base
+          : functional::multiplies<Left, Right>
+        {};
+
+        template<typename Left, typename Right, typename LeftTag = typename tag<Left>::type, typename RightTag = typename tag<Right>::type>
+        struct outer_product
+          : outer_product_base<Left, Right, void>
+        {};
+
+        template<typename Left, typename Right>
+        struct outer_product<Left, Right, std_vector_tag, std_vector_tag>
+          : std::binary_function<
+                Left
+              , Right
+              , ublas::matrix<
+                    typename functional::multiplies<
+                        typename Left::value_type
+                      , typename Right::value_type
+                    >::result_type
+                >
+            >
+        {
+            typedef 
+                ublas::matrix<
+                    typename functional::multiplies<
+                        typename Left::value_type
+                      , typename Right::value_type
+                    >::result_type
+                >
+            result_type;
+
+            result_type
+            operator ()(Left & left, Right & right) const
+            {
+                std::size_t left_size = left.size();
+                std::size_t right_size = right.size();
+                result_type result(left_size, right_size);
+                for (std::size_t i = 0; i < left_size; ++i)
+                    for (std::size_t j = 0; j < right_size; ++j)   
+                        result(i,j) = numeric::multiplies(left[i], right[j]);
+                return result;
+            }
+        };
+    }
+
+    namespace op
+    {
+        struct outer_product
+          : boost::detail::function2<functional::outer_product<_1, _2, functional::tag<_1>, functional::tag<_2> > >
+        {};
+    }
+
+    namespace
+    {
+        op::outer_product const &outer_product = boost::detail::pod_singleton<op::outer_product>::instance;
+    }
+
+}}
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // covariance_impl
+    //
+    /**
+        @brief Covariance Estimator
+
+        An iterative Monte Carlo estimator for the covariance \f$\mathrm{Cov}(X,X')\f$, where \f$X\f$ is a sample 
+        and \f$X'\f$ is a variate, is given by:
+
+        \f[
+            \hat{c}_n = \frac{n-1}{n} \hat{c}_{n-1} + \frac{1}{n-1}(X_n - \hat{\mu}_n)(X_n' - \hat{\mu}_n'),\quad n\ge2,\quad\hat{c}_1 = 0,
+        \f]
+        
+        \f$\hat{\mu}_n\f$ and \f$\hat{\mu}_n'\f$ being the means of the samples and variates.
+    */
+    template<typename Sample, typename VariateType, typename VariateTag>
+    struct covariance_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type sample_type;
+        typedef typename numeric::functional::average<VariateType, std::size_t>::result_type variate_type;
+        // for boost::result_of
+        typedef typename numeric::functional::outer_product<sample_type, variate_type>::result_type result_type;
+    
+        template<typename Args>
+        covariance_impl(Args const &args)
+          : cov_(
+                numeric::outer_product(
+                    numeric::average(args[sample | Sample()], (std::size_t)1)
+                  , numeric::average(args[parameter::keyword<VariateTag>::get() | VariateType()], (std::size_t)1)
+                )
+            )
+        {
+        }
+        
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            std::size_t cnt = count(args);
+            
+            if (cnt > 1)
+            {
+                extractor<tag::mean_of_variates<VariateType, VariateTag> > const some_mean_of_variates = {};
+                
+                this->cov_ = this->cov_*(cnt-1.)/cnt
+                           + numeric::outer_product(
+                                 some_mean_of_variates(args) - args[parameter::keyword<VariateTag>::get()]
+                               , mean(args) - args[sample]
+                             ) / (cnt-1.);
+            }
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->cov_;
+        }
+
+    private:
+        result_type cov_;
+    };
+    
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::covariance
+//
+namespace tag
+{
+    template<typename VariateType, typename VariateTag>
+    struct covariance
+      : depends_on<count, mean, mean_of_variates<VariateType, VariateTag> >
+    {
+        typedef accumulators::impl::covariance_impl<mpl::_1, VariateType, VariateTag> impl;
+    };  
+    
+    struct abstract_covariance 
+      : depends_on<>
+    {
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::covariance
+//
+namespace extract
+{
+    extractor<tag::abstract_covariance> const covariance = {};
+}
+
+using extract::covariance;
+
+template<typename VariateType, typename VariateTag>
+struct feature_of<tag::covariance<VariateType, VariateTag> >
+  : feature_of<tag::abstract_covariance>
+{
+};
+
+// So that covariance can be automatically substituted with
+// weighted_covariance when the weight parameter is non-void.
+template<typename VariateType, typename VariateTag>
+struct as_weighted_feature<tag::covariance<VariateType, VariateTag> >
+{
+    typedef tag::weighted_covariance<VariateType, VariateTag> type;
+};
+
+template<typename VariateType, typename VariateTag>
+struct feature_of<tag::weighted_covariance<VariateType, VariateTag> >
+  : feature_of<tag::covariance<VariateType, VariateTag> >
+{};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/density.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/density.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,241 @@
+
+///////////////////////////////////////////////////////////////////////////////
+// density.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_DENSITY_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_DENSITY_HPP_DE_01_01_2006
+
+#include <vector>
+#include <limits>
+#include <functional>
+#include <boost/range.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/max.hpp>
+#include <boost/accumulators/statistics/min.hpp>
+
+namespace boost { namespace accumulators
+{
+
+///////////////////////////////////////////////////////////////////////////////
+// cache_size and num_bins named parameters
+//
+BOOST_PARAMETER_NESTED_KEYWORD(tag, density_cache_size, cache_size)
+BOOST_PARAMETER_NESTED_KEYWORD(tag, density_num_bins, num_bins)
+
+namespace impl
+{       
+    ///////////////////////////////////////////////////////////////////////////////
+    // density_impl
+    //  density histogram
+    /**
+        @brief Histogram density estimator
+
+        The histogram density estimator returns a histogram of the sample distribution. The positions and sizes of the bins 
+        are determined using a specifiable number of cached samples (cache_size). The range between the minimum and the 
+        maximum of the cached samples is subdivided into a specifiable number of bins (num_bins) of same size. Additionally, 
+        an under- and an overflow bin is added to capture future under- and overflow samples. Once the bins are determined, 
+        the cached samples and all subsequent samples are added to the correct bins. At the end, a range of std::pair is 
+        return, where each pair contains the position of the bin (lower bound) and the samples count (normalized with the 
+        total number of samples).
+                
+        @param  density_cache_size Number of first samples used to determine min and max.
+        @param  density_num_bins Number of bins (two additional bins collect under- and overflow samples). 
+    */
+    template<typename Sample>
+    struct density_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        typedef std::vector<std::pair<float_type, float_type> > histogram_type;
+        typedef std::vector<float_type> array_type;
+        // for boost::result_of
+        typedef iterator_range<typename histogram_type::iterator> result_type;
+        
+        template<typename Args>
+        density_impl(Args const &args)
+            : cache_size(args[density_cache_size])
+            , cache(cache_size)
+            , num_bins(args[density_num_bins])
+            , samples_in_bin(num_bins + 2, 0.)
+            , bin_positions(num_bins + 2)
+            , histogram(
+                num_bins + 2
+              , std::make_pair(
+                    numeric::average(args[sample | Sample()],(std::size_t)1)
+                  , numeric::average(args[sample | Sample()],(std::size_t)1)
+                )
+              )
+            , is_dirty(true)
+        {
+        }
+        
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            this->is_dirty = true;
+            
+            std::size_t cnt = count(args);
+            
+            // Fill up cache with cache_size first samples
+            if (cnt <= this->cache_size)
+            {
+                this->cache[cnt - 1] = args[sample];
+            }
+            
+            // Once cache_size samples have been accumulated, create num_bins bins of same size between 
+            // the minimum and maximum of the cached samples as well as an under- and and an overflow bin. 
+            // Store their lower bounds (bin_positions) and fill the bins with the cached samples (samples_in_bin).
+            if (cnt == this->cache_size)
+            {
+                float_type minimum = numeric::average((min)(args), (std::size_t)1);
+                float_type maximum = numeric::average((max)(args), (std::size_t)1);
+                float_type bin_size = numeric::average(maximum - minimum, this->num_bins ); 
+                
+                // determine bin positions (their lower bounds)
+                for (std::size_t i = 0; i < this->num_bins + 2; ++i) 
+                {
+                    this->bin_positions[i] = minimum + (i - 1.) * bin_size;
+                }
+                
+                for (typename array_type::const_iterator iter = this->cache.begin(); iter != this->cache.end(); ++iter)
+                {
+                    if (*iter < this->bin_positions[1])
+                    {
+                        ++(this->samples_in_bin[0]);
+                    }
+                    else if (*iter >= this->bin_positions[this->num_bins + 1])
+                    {
+                        ++(this->samples_in_bin[this->num_bins + 1]);
+                    }    
+                    else
+                    {
+                        typename array_type::iterator it = std::upper_bound(
+                            this->bin_positions.begin()
+                          , this->bin_positions.end()
+                          , *iter
+                        );
+                        
+                        std::size_t d = std::distance(this->bin_positions.begin(), it);
+                        ++(this->samples_in_bin[d - 1]);
+                    }
+                }
+            }
+            // Add each subsequent sample to the correct bin
+            else if (cnt > this->cache_size)
+            {
+                if (args[sample] < this->bin_positions[1])
+                {
+                    ++(this->samples_in_bin[0]);
+                }
+                else if (args[sample] >= this->bin_positions[this->num_bins + 1])
+                {
+                    ++(this->samples_in_bin[this->num_bins + 1]);
+                }
+                else
+                {
+                    typename array_type::iterator it = std::upper_bound(
+                        this->bin_positions.begin()
+                      , this->bin_positions.end()
+                      , args[sample]
+                    );
+                    
+                    std::size_t d = std::distance(this->bin_positions.begin(), it);
+                    ++(this->samples_in_bin[d - 1]);
+                }
+            }        
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            if (this->is_dirty)
+            {
+                this->is_dirty = false;
+            
+                // creates a vector of std::pair where each pair i holds
+                // the values bin_positions[i] (x-axis of histogram) and
+                // samples_in_bin[i] / cnt (y-axis of histogram).
+    
+                for (std::size_t i = 0; i < this->num_bins + 2; ++i)
+                {
+                    this->histogram[i] = std::make_pair(this->bin_positions[i], numeric::average(this->samples_in_bin[i], count(args)));
+                }
+            }
+            // returns a range of pairs            
+            return make_iterator_range(this->histogram);
+        }
+
+    private:
+        std::size_t            cache_size;      // number of cached samples
+        array_type             cache;           // cache to store the first cache_size samples
+        std::size_t            num_bins;        // number of bins
+        array_type             samples_in_bin;  // number of samples in each bin
+        array_type             bin_positions;   // lower bounds of bins
+        mutable histogram_type histogram;       // histogram
+        mutable bool is_dirty;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::density
+//
+namespace tag
+{
+    struct density
+      : depends_on<count, min, max>
+      , density_cache_size
+      , density_num_bins
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::density_impl<mpl::_1> impl;
+        
+        #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED
+        /// tag::density::cache_size named parameter
+        /// tag::density::num_bins named parameter
+        static boost::parameter::keyword<density_cache_size> const cache_size;
+        static boost::parameter::keyword<density_num_bins> const num_bins;
+        #endif
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::density
+//
+namespace extract
+{
+    extractor<tag::density> const density = {};
+}
+
+using extract::density;
+
+// So that density can be automatically substituted 
+// with weighted_density when the weight parameter is non-void.
+template<>
+struct as_weighted_feature<tag::density>
+{
+    typedef tag::weighted_density type;
+};
+
+template<>
+struct feature_of<tag::weighted_density>
+  : feature_of<tag::density>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/error_of.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/error_of.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,99 @@
+///////////////////////////////////////////////////////////////////////////////
+// error_of.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_ERROR_OF_HPP_EAN_29_11_2005
+#define BOOST_ACCUMULATORS_STATISTICS_ERROR_OF_HPP_EAN_29_11_2005
+
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    /// INTERNAL ONLY
+    ///
+    template<typename Feature>
+    struct this_feature_has_no_error_calculation
+      : mpl::false_
+    {
+    };
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // error_of_impl
+    /// INTERNAL ONLY
+    ///
+    template<typename Sample, typename Feature>
+    struct error_of_impl
+      : accumulator_base
+    {
+        // TODO: specialize this on the specific features that have errors we're
+        // interested in.
+        BOOST_MPL_ASSERT((this_feature_has_no_error_calculation<Feature>));
+
+        // for boost::result_of
+        typedef int result_type;
+
+        error_of_impl(dont_care)
+        {
+        }
+
+        result_type result(dont_care) const
+        {
+            return 0;
+        }
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::error_of
+//
+namespace tag
+{
+    template<typename Feature>
+    struct error_of
+      : depends_on<Feature>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::error_of_impl<mpl::_1, Feature> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::error_of
+//
+namespace extract
+{
+    BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, error_of, (typename))
+}
+
+using extract::error_of;
+
+// make tag::error_of<tag::feature(modifier)> work
+template<typename Feature>
+struct as_feature<tag::error_of<Feature> >
+{
+    typedef tag::error_of<typename as_feature<Feature>::type> type;
+};
+
+// make error_of<tag::mean> work with non-void weights (should become
+// error_of<tag::weighted_mean>
+template<typename Feature>
+struct as_weighted_feature<tag::error_of<Feature> >
+{
+    typedef tag::error_of<typename as_weighted_feature<Feature>::type> type;
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/error_of_mean.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/error_of_mean.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,73 @@
+///////////////////////////////////////////////////////////////////////////////
+// error_of.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_ERROR_OF_MEAN_HPP_EAN_27_03_2006
+#define BOOST_ACCUMULATORS_STATISTICS_ERROR_OF_MEAN_HPP_EAN_27_03_2006
+
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/error_of.hpp>
+#include <boost/accumulators/statistics/variance.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // error_of_mean_impl
+    template<typename Sample, typename Variance>
+    struct error_of_mean_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type result_type;
+
+        error_of_mean_impl(dont_care) {}
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            using namespace std;
+            extractor<Variance> const variance = {};
+            return sqrt(numeric::average(variance(args), count(args) - 1));
+        }
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::error_of
+//
+namespace tag
+{
+    template<>
+    struct error_of<mean>
+      : depends_on<variance, count>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::error_of_mean_impl<mpl::_1, variance> impl;
+    };
+
+    template<>
+    struct error_of<immediate_mean>
+      : depends_on<immediate_variance, count>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::error_of_mean_impl<mpl::_1, immediate_variance> impl;
+    };
+}
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/extended_p_square.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/extended_p_square.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,292 @@
+///////////////////////////////////////////////////////////////////////////////
+// extended_p_square.hpp
+//
+//  Copyright 2005 Daniel Egloff. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_EXTENDED_SINGLE_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_EXTENDED_SINGLE_HPP_DE_01_01_2006
+
+#include <vector>
+#include <functional>
+#include <boost/range/begin.hpp>
+#include <boost/range/end.hpp>
+#include <boost/range/iterator_range.hpp>
+#include <boost/iterator/transform_iterator.hpp>
+#include <boost/iterator/counting_iterator.hpp>
+#include <boost/iterator/permutation_iterator.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/times2_iterator.hpp>
+
+namespace boost { namespace accumulators
+{
+///////////////////////////////////////////////////////////////////////////////
+// probabilities named parameter
+//
+BOOST_PARAMETER_NESTED_KEYWORD(tag, extended_p_square_probabilities, probabilities)
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // extended_p_square_impl
+    //  multiple quantile estimation
+    /**
+        @brief Multiple quantile estimation with the extended \f$P^2\f$ algorithm
+
+        Extended \f$P^2\f$ algorithm for estimation of several quantiles without storing samples.
+        Assume that \f$m\f$ quantiles \f$\xi_{p_1}, \ldots, \xi_{p_m}\f$ are to be estimated. 
+        Instead of storing the whole sample cumulative distribution, the algorithm maintains only 
+        \f$m+2\f$ principal markers and \f$m+1\f$ middle markers, whose positions are updated 
+        with each sample and whose heights are adjusted (if necessary) using a piecewise-parablic 
+        formula. The heights of these central markers are the current estimates of the quantiles 
+        and returned as an iterator range.
+
+        For further details, see
+        
+        K. E. E. Raatikainen, Simultaneous estimation of several quantiles, Simulation, Volume 49,
+        Number 4 (October), 1986, p. 159-164.
+
+        The extended \f$ P^2 \f$ algorithm generalizess the \f$ P^2 \f$ algorithm of
+
+        R. Jain and I. Chlamtac, The P^2 algorithmus for dynamic calculation of quantiles and
+        histograms without storing observations, Communications of the ACM,
+        Volume 28 (October), Number 10, 1985, p. 1076-1085.
+
+        @param extended_p_square_probabilities A vector of quantile probabilities.
+    */
+    template<typename Sample>
+    struct extended_p_square_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        typedef std::vector<float_type> array_type;
+        // for boost::result_of
+        typedef iterator_range<
+            detail::lvalue_index_iterator<
+                permutation_iterator<
+                    typename array_type::const_iterator
+                  , detail::times2_iterator
+                >
+            >
+        > result_type;
+        
+        template<typename Args>
+        extended_p_square_impl(Args const &args)
+          : probabilities(
+                boost::begin(args[extended_p_square_probabilities])
+              , boost::end(args[extended_p_square_probabilities])
+            )
+          , heights(2 * probabilities.size() + 3)
+          , actual_positions(heights.size())
+          , desired_positions(heights.size())
+          , positions_increments(heights.size())
+        {
+            std::size_t num_quantiles = this->probabilities.size();
+            std::size_t num_markers = this->heights.size();
+
+            for(std::size_t i = 0; i < num_markers; ++i)
+            {
+                this->actual_positions[i] = i + 1;
+            }
+
+            this->positions_increments[0] = 0.;
+            this->positions_increments[num_markers - 1] = 1.;
+
+            for(std::size_t i = 0; i < num_quantiles; ++i)
+            {
+                this->positions_increments[2 * i + 2] = probabilities[i];
+            }
+
+            for(std::size_t i = 0; i <= num_quantiles; ++i)
+            {
+                this->positions_increments[2 * i + 1] =
+                    0.5 * (this->positions_increments[2 * i] + this->positions_increments[2 * i + 2]);
+            }
+
+            for(std::size_t i = 0; i < num_markers; ++i)
+            {
+                this->desired_positions[i] = 1. + 2. * (num_quantiles + 1.) * this->positions_increments[i];
+            }
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            std::size_t cnt = count(args);
+
+            // m+2 principal markers and m+1 middle markers
+            std::size_t num_markers = 2 * this->probabilities.size() + 3;
+                        
+            // first accumulate num_markers samples
+            if(cnt <= num_markers)
+            {
+                this->heights[cnt - 1] = args[sample];
+
+                // complete the initialization of heights by sorting
+                if(cnt == num_markers)
+                {
+                    std::sort(this->heights.begin(), this->heights.end());
+                }
+            }
+            else
+            {
+                std::size_t sample_cell = 1;
+
+                // find cell k = sample_cell such that heights[k-1] <= sample < heights[k]
+                if(args[sample] < this->heights[0])
+                {
+                    this->heights[0] = args[sample];
+                    sample_cell = 1;
+                }
+                else if(args[sample] >= this->heights[num_markers - 1])
+                {
+                    this->heights[num_markers - 1] = args[sample];
+                    sample_cell = num_markers - 1;
+                }
+                else
+                {
+                    typedef typename array_type::iterator iterator;
+                    iterator it = std::upper_bound(
+                        this->heights.begin()
+                      , this->heights.end()
+                      , args[sample]
+                    );
+
+                    sample_cell = std::distance(this->heights.begin(), it);
+                }
+
+                // update actual positions of all markers above sample_cell index
+                for(std::size_t i = sample_cell; i < num_markers; ++i)
+                {
+                    ++this->actual_positions[i];
+                }
+
+                // update desired positions of all markers
+                for(std::size_t i = 0; i < num_markers; ++i)
+                {
+                    this->desired_positions[i] += this->positions_increments[i];
+                }
+
+                // adjust heights and actual positions of markers 1 to num_markers-2 if necessary
+                for(std::size_t i = 1; i <= num_markers - 2; ++i)
+                {
+                    // offset to desired position
+                    float_type d = this->desired_positions[i] - this->actual_positions[i];
+
+                    // offset to next position
+                    float_type dp = this->actual_positions[i+1] - this->actual_positions[i];
+
+                    // offset to previous position
+                    float_type dm = this->actual_positions[i-1] - this->actual_positions[i];
+
+                    // height ds
+                    float_type hp = (this->heights[i+1] - this->heights[i]) / dp;
+                    float_type hm = (this->heights[i-1] - this->heights[i]) / dm;
+
+                    if((d >= 1 && dp > 1) || (d <= -1 && dm < -1))
+                    {
+                        short sign_d = static_cast<short>(d / std::abs(d));
+
+                        float_type h = this->heights[i] + sign_d / (dp - dm) * ((sign_d - dm)*hp
+                                     + (dp - sign_d) * hm);
+
+                        // try adjusting heights[i] using p-squared formula
+                        if(this->heights[i - 1] < h && h < this->heights[i + 1])
+                        {
+                            this->heights[i] = h;
+                        }
+                        else
+                        {
+                            // use linear formula
+                            if(d > 0)
+                            {
+                                this->heights[i] += hp;
+                            }
+                            if(d < 0)
+                            {
+                                this->heights[i] -= hm;
+                            }
+                        }
+                        this->actual_positions[i] += sign_d;
+                    }
+                }
+            }
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            // for i in [1,probabilities.size()], return heights[i * 2]
+            detail::times2_iterator idx_begin = detail::make_times2_iterator(1);
+            detail::times2_iterator idx_end = detail::make_times2_iterator(this->probabilities.size() + 1);
+
+            return result_type(
+                make_permutation_iterator(this->heights.begin(), idx_begin)
+              , make_permutation_iterator(this->heights.begin(), idx_end)
+            );
+        }
+
+    private:
+        array_type probabilities;         // the quantile probabilities
+        array_type heights;               // q_i
+        array_type actual_positions;      // n_i
+        array_type desired_positions;     // d_i
+        array_type positions_increments;  // f_i
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::extended_p_square
+//
+namespace tag
+{
+    struct extended_p_square
+      : depends_on<count>
+      , extended_p_square_probabilities
+    {
+        typedef accumulators::impl::extended_p_square_impl<mpl::_1> impl;
+
+        #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED
+        /// tag::extended_p_square::probabilities named paramter
+        static boost::parameter::keyword<tag::probabilities> const probabilities;
+        #endif
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::extended_p_square
+//
+namespace extract
+{
+    extractor<tag::extended_p_square> const extended_p_square = {};
+}
+
+using extract::extended_p_square;
+
+// So that extended_p_square can be automatically substituted with 
+// weighted_extended_p_square when the weight parameter is non-void
+template<>
+struct as_weighted_feature<tag::extended_p_square>
+{
+    typedef tag::weighted_extended_p_square type;
+};
+
+template<>
+struct feature_of<tag::weighted_extended_p_square>
+  : feature_of<tag::extended_p_square>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/extended_p_square_quantile.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/extended_p_square_quantile.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,305 @@
+///////////////////////////////////////////////////////////////////////////////
+// extended_p_square_quantile.hpp
+//
+//  Copyright 2005 Daniel Egloff. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_EXTENDED_SINGLE_QUANTILE_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_EXTENDED_SINGLE_QUANTILE_HPP_DE_01_01_2006
+
+#include <vector>
+#include <functional>
+#include <boost/range/begin.hpp>
+#include <boost/range/end.hpp>
+#include <boost/range/iterator_range.hpp>
+#include <boost/iterator/transform_iterator.hpp>
+#include <boost/iterator/counting_iterator.hpp>
+#include <boost/iterator/permutation_iterator.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
+#include <boost/accumulators/statistics/extended_p_square.hpp>
+#include <boost/accumulators/statistics/weighted_extended_p_square.hpp>
+#include <boost/accumulators/statistics/times2_iterator.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // extended_p_square_quantile_impl
+    //  single quantile estimation
+    /**
+        @brief Quantile estimation using the extended \f$P^2\f$ algorithm for weighted and unweighted samples
+
+        Uses the quantile estimates calculated by the extended \f$P^2\f$ algorithm to compute 
+        intermediate quantile estimates by means of quadratic interpolation.
+
+        @param quantile_probability The probability of the quantile to be estimated.
+    */
+    template<typename Sample, typename Impl1, typename Impl2> // Impl1: weighted/unweighted // Impl2: linear/quadratic
+    struct extended_p_square_quantile_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        typedef std::vector<float_type> array_type;
+        typedef iterator_range<
+            detail::lvalue_index_iterator<
+                permutation_iterator<
+                    typename array_type::const_iterator
+                  , detail::times2_iterator
+                >
+            >
+        > range_type;
+        // for boost::result_of
+        typedef float_type result_type;
+        
+        template<typename Args>
+        extended_p_square_quantile_impl(Args const &args)
+          : probabilities(
+                boost::begin(args[extended_p_square_probabilities])
+              , boost::end(args[extended_p_square_probabilities])
+            )
+        {
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            typedef
+                typename mpl::if_<
+                    is_same<Impl1, weighted>
+                  , tag::weighted_extended_p_square
+                  , tag::extended_p_square
+                >::type
+            extended_p_square_tag;
+            
+            extractor<extended_p_square_tag> const some_extended_p_square = {};
+        
+            array_type heights(some_extended_p_square(args).size());
+            std::copy(some_extended_p_square(args).begin(), some_extended_p_square(args).end(), heights.begin());
+
+            this->probability = args[quantile_probability];
+            
+            typename array_type::const_iterator iter_probs = std::lower_bound(this->probabilities.begin(), this->probabilities.end(), this->probability);
+            std::size_t dist = std::distance(this->probabilities.begin(), iter_probs);
+            typename array_type::const_iterator iter_heights = heights.begin() + dist;
+            
+            // If this->probability is not in a valid range return NaN or throw exception
+            if (this->probability < *this->probabilities.begin() || this->probability > *(this->probabilities.end() - 1))
+            {
+                if (std::numeric_limits<result_type>::has_quiet_NaN)
+                {
+                    return std::numeric_limits<result_type>::quiet_NaN();
+                }
+                else
+                {
+                    std::ostringstream msg;
+                    msg << "probability = " << this->probability << " is not in valid range (";
+                    msg << *this->probabilities.begin() << ", " << *(this->probabilities.end() - 1) << ")";
+                    boost::throw_exception(std::runtime_error(msg.str()));
+                    return Sample(0);
+                }
+
+            }
+            
+            if (*iter_probs == this->probability)
+            {
+                return heights[dist];
+            }
+            else
+            {
+                result_type result;
+            
+                if (is_same<Impl2, linear>::value)
+                {
+                    /////////////////////////////////////////////////////////////////////////////////
+                    // LINEAR INTERPOLATION
+                    //
+                    float_type p1 = *iter_probs;
+                    float_type p0 = *(iter_probs - 1);
+                    float_type h1 = *iter_heights;
+                    float_type h0 = *(iter_heights - 1);
+                    
+                    float_type a = numeric::average(h1 - h0, p1 - p0);
+                    float_type b = h1 - p1 * a;
+                    
+                    result = a * this->probability + b;
+                }
+                else
+                {
+                    /////////////////////////////////////////////////////////////////////////////////
+                    // QUADRATIC INTERPOLATION
+                    //
+                    float_type p0, p1, p2;
+                    float_type h0, h1, h2;
+                    
+                    if ( (dist == 1 || *iter_probs - this->probability <= this->probability - *(iter_probs - 1) ) && dist != this->probabilities.size() - 1 )
+                    {
+                        p0 = *(iter_probs - 1);
+                        p1 = *iter_probs;
+                        p2 = *(iter_probs + 1);
+                        h0 = *(iter_heights - 1);
+                        h1 = *iter_heights;
+                        h2 = *(iter_heights + 1);
+                    }
+                    else
+                    {
+                        p0 = *(iter_probs - 2);
+                        p1 = *(iter_probs - 1);
+                        p2 = *iter_probs;
+                        h0 = *(iter_heights - 2);
+                        h1 = *(iter_heights - 1);
+                        h2 = *iter_heights;
+                    }
+                    
+                    float_type hp21 = numeric::average(h2 - h1, p2 - p1);
+                    float_type hp10 = numeric::average(h1 - h0, p1 - p0);
+                    float_type p21  = numeric::average(p2 * p2 - p1 * p1, p2 - p1);
+                    float_type p10  = numeric::average(p1 * p1 - p0 * p0, p1 - p0);
+                    
+                    float_type a = numeric::average(hp21 - hp10, p21 - p10);
+                    float_type b = hp21 - a * p21;
+                    float_type c = h2 - a * p2 * p2 - b * p2;
+                    
+                    result = a * this->probability * this-> probability + b * this->probability + c;
+                }
+                
+                return result;
+            }
+            
+        }
+    private:
+    
+        array_type probabilities;
+        mutable float_type probability;
+    
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::extended_p_square_quantile
+//
+namespace tag
+{
+    struct extended_p_square_quantile
+      : depends_on<extended_p_square>
+    {
+        typedef accumulators::impl::extended_p_square_quantile_impl<mpl::_1, unweighted, linear> impl;
+    };
+    struct extended_p_square_quantile_quadratic
+      : depends_on<extended_p_square>
+    {
+        typedef accumulators::impl::extended_p_square_quantile_impl<mpl::_1, unweighted, quadratic> impl;
+    };
+    struct weighted_extended_p_square_quantile
+      : depends_on<weighted_extended_p_square>
+    {
+        typedef accumulators::impl::extended_p_square_quantile_impl<mpl::_1, weighted, linear> impl;
+    };
+    struct weighted_extended_p_square_quantile_quadratic
+      : depends_on<weighted_extended_p_square>
+    {
+        typedef accumulators::impl::extended_p_square_quantile_impl<mpl::_1, weighted, quadratic> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::extended_p_square_quantile
+// extract::weighted_extended_p_square_quantile
+//
+namespace extract
+{
+    extractor<tag::extended_p_square_quantile> const extended_p_square_quantile = {};
+    extractor<tag::extended_p_square_quantile_quadratic> const extended_p_square_quantile_quadratic = {};
+    extractor<tag::weighted_extended_p_square_quantile> const weighted_extended_p_square_quantile = {};
+    extractor<tag::weighted_extended_p_square_quantile_quadratic> const weighted_extended_p_square_quantile_quadratic = {};
+}
+
+using extract::extended_p_square_quantile;
+using extract::extended_p_square_quantile_quadratic;
+using extract::weighted_extended_p_square_quantile;
+using extract::weighted_extended_p_square_quantile_quadratic;
+
+// extended_p_square_quantile(linear) -> extended_p_square_quantile
+template<>
+struct as_feature<tag::extended_p_square_quantile(linear)>
+{
+    typedef tag::extended_p_square_quantile type;
+};
+
+// extended_p_square_quantile(quadratic) -> extended_p_square_quantile_quadratic
+template<>
+struct as_feature<tag::extended_p_square_quantile(quadratic)>
+{
+    typedef tag::extended_p_square_quantile_quadratic type;
+};
+
+// weighted_extended_p_square_quantile(linear) -> weighted_extended_p_square_quantile
+template<>
+struct as_feature<tag::weighted_extended_p_square_quantile(linear)>
+{
+    typedef tag::weighted_extended_p_square_quantile type;
+};
+
+// weighted_extended_p_square_quantile(quadratic) -> weighted_extended_p_square_quantile_quadratic
+template<>
+struct as_feature<tag::weighted_extended_p_square_quantile(quadratic)>
+{
+    typedef tag::weighted_extended_p_square_quantile_quadratic type;
+};
+
+// for the purposes of feature-based dependency resolution,
+// extended_p_square_quantile and weighted_extended_p_square_quantile 
+// provide the same feature as quantile
+template<>
+struct feature_of<tag::extended_p_square_quantile>
+  : feature_of<tag::quantile>
+{
+};
+template<>
+struct feature_of<tag::extended_p_square_quantile_quadratic>
+  : feature_of<tag::quantile>
+{
+};
+// So that extended_p_square_quantile can be automatically substituted with 
+// weighted_extended_p_square_quantile when the weight parameter is non-void
+template<>
+struct as_weighted_feature<tag::extended_p_square_quantile>
+{
+    typedef tag::weighted_extended_p_square_quantile type;
+};
+
+template<>
+struct feature_of<tag::weighted_extended_p_square_quantile>
+  : feature_of<tag::extended_p_square_quantile>
+{
+};
+
+// So that extended_p_square_quantile_quadratic can be automatically substituted with 
+// weighted_extended_p_square_quantile_quadratic when the weight parameter is non-void
+template<>
+struct as_weighted_feature<tag::extended_p_square_quantile_quadratic>
+{
+    typedef tag::weighted_extended_p_square_quantile_quadratic type;
+};
+template<>
+struct feature_of<tag::weighted_extended_p_square_quantile_quadratic>
+  : feature_of<tag::extended_p_square_quantile_quadratic>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/kurtosis.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/kurtosis.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,110 @@
+///////////////////////////////////////////////////////////////////////////////
+// kurtosis.hpp
+//
+//  Copyright 2006 Olivier Gygi, Daniel Egloff. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_KURTOSIS_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_KURTOSIS_HPP_EAN_28_10_2005
+
+#include <limits>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics/mean.hpp>
+#include <boost/accumulators/statistics/moment.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // kurtosis_impl
+    /**
+        @brief Kurtosis estimation
+
+        The kurtosis of a sample distribution is defined as the ratio of the 4th central moment and the square of the 2nd central 
+        moment (the variance) of the samples, minus 3. The term \f$ -3 \f$ is added in order to ensure that the normal distribution 
+        has zero kurtosis. The kurtosis can also be expressed by the simple moments:
+        
+        \f[
+            \hat{g}_2 = 
+                \frac
+                {\widehat{m}_n^{(4)}-4\widehat{m}_n^{(3)}\hat{\mu}_n+6\widehat{m}_n^{(2)}\hat{\mu}_n^2-3\hat{\mu}_n^4}
+                {\left(\widehat{m}_n^{(2)} - \hat{\mu}_n^{2}\right)^2} - 3,
+        \f]
+        
+        where \f$ \widehat{m}_n^{(i)} \f$ are the \f$ i \f$-th moment and \f$ \hat{\mu}_n \f$ the mean (first moment) of the 
+        \f$ n \f$ samples.
+    */
+    template<typename Sample>
+    struct kurtosis_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef typename numeric::functional::average<Sample, Sample>::result_type result_type;
+
+        kurtosis_impl(dont_care) {}
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return numeric::average(
+                        moment<4>(args)
+                        - 4. * moment<3>(args) * mean(args)
+                        + 6. * moment<2>(args) * mean(args) * mean(args) 
+                        - 3. * mean(args) * mean(args) * mean(args) * mean(args)
+                      , ( moment<2>(args) - mean(args) * mean(args) ) 
+                        * ( moment<2>(args) - mean(args) * mean(args) ) 
+                    ) - 3.;
+        }
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::kurtosis
+//
+namespace tag
+{
+    struct kurtosis
+      : depends_on<mean, moment<2>, moment<3>, moment<4> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::kurtosis_impl<mpl::_1> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::kurtosis
+//
+namespace extract
+{
+    extractor<tag::kurtosis> const kurtosis = {};
+}
+
+using extract::kurtosis;
+
+// So that kurtosis can be automatically substituted with 
+// weighted_kurtosis when the weight parameter is non-void
+template<>
+struct as_weighted_feature<tag::kurtosis>
+{
+    typedef tag::weighted_kurtosis type;
+};
+
+template<>
+struct feature_of<tag::weighted_kurtosis>
+  : feature_of<tag::kurtosis>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/max.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/max.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,83 @@
+///////////////////////////////////////////////////////////////////////////////
+// max.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_MAX_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_MAX_HPP_EAN_28_10_2005
+
+#include <limits>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // max_impl
+    template<typename Sample>
+    struct max_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef Sample result_type;
+
+        template<typename Args>
+        max_impl(Args const &args)
+          : max_(numeric::as_min(args[sample | Sample()]))
+        {
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            numeric::max_assign(this->max_, args[sample]);
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->max_;
+        }
+
+    private:
+        Sample max_;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::max
+//
+namespace tag
+{
+    struct max
+      : depends_on<>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::max_impl<mpl::_1> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::max
+//
+namespace extract
+{
+    extractor<tag::max> const max = {};
+}
+
+using extract::max;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/mean.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/mean.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,297 @@
+///////////////////////////////////////////////////////////////////////////////
+// mean.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_MEAN_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_MEAN_HPP_EAN_28_10_2005
+
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/sum.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // mean_impl
+    //      lazy, by default
+    template<typename Sample, typename SumFeature>
+    struct mean_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type result_type;
+
+        mean_impl(dont_care) {}
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            extractor<SumFeature> sum;
+            return numeric::average(sum(args), count(args));
+        }
+    };
+
+    template<typename Sample, typename Tag>
+    struct immediate_mean_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type result_type;
+
+        template<typename Args>
+        immediate_mean_impl(Args const &args)
+          : mean(numeric::average(args[sample | Sample()], numeric::one<std::size_t>::value))
+        {
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            std::size_t cnt = count(args);
+            this->mean = numeric::average(
+                (this->mean * (cnt - 1)) + args[parameter::keyword<Tag>::get()]
+              , cnt
+            );
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->mean;
+        }
+
+    private:
+        result_type mean;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::mean
+// tag::immediate_mean
+// tag::mean_of_weights
+// tag::immediate_mean_of_weights
+// tag::mean_of_variates
+// tag::immediate_mean_of_variates
+//
+namespace tag
+{
+    struct mean
+      : depends_on<count, sum>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::mean_impl<mpl::_1, sum> impl;
+    };
+    struct immediate_mean
+      : depends_on<count>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::immediate_mean_impl<mpl::_1, tag::sample> impl;
+    };
+    struct mean_of_weights
+      : depends_on<count, sum_of_weights>
+    {
+        typedef mpl::true_ is_weight_accumulator;
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::mean_impl<mpl::_2, sum_of_weights> impl;
+    };
+    struct immediate_mean_of_weights
+      : depends_on<count>
+    {
+        typedef mpl::true_ is_weight_accumulator;
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::immediate_mean_impl<mpl::_2, tag::weight> impl;
+    };
+    template<typename VariateType, typename VariateTag>
+    struct mean_of_variates
+      : depends_on<count, sum_of_variates<VariateType, VariateTag> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef mpl::always<accumulators::impl::mean_impl<VariateType, sum_of_variates<VariateType, VariateTag> > > impl;
+    };
+    template<typename VariateType, typename VariateTag>
+    struct immediate_mean_of_variates
+      : depends_on<count>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef mpl::always<accumulators::impl::immediate_mean_impl<VariateType, VariateTag> > impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::mean
+// extract::mean_of_weights
+// extract::mean_of_variates
+//
+namespace extract
+{
+    extractor<tag::mean> const mean = {};
+    extractor<tag::mean_of_weights> const mean_of_weights = {};
+    BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, mean_of_variates, (typename)(typename));
+}
+
+using extract::mean;
+using extract::mean_of_weights;
+using extract::mean_of_variates;
+
+// mean(lazy) -> mean
+template<>
+struct as_feature<tag::mean(lazy)>
+{
+    typedef tag::mean type;
+};
+
+// mean(immediate) -> immediate_mean
+template<>
+struct as_feature<tag::mean(immediate)>
+{
+    typedef tag::immediate_mean type;
+};
+
+// mean_of_weights(lazy) -> mean_of_weights
+template<>
+struct as_feature<tag::mean_of_weights(lazy)>
+{
+    typedef tag::mean_of_weights type;
+};
+
+// mean_of_weights(immediate) -> immediate_mean_of_weights
+template<>
+struct as_feature<tag::mean_of_weights(immediate)>
+{
+    typedef tag::immediate_mean_of_weights type;
+};
+
+// mean_of_variates<VariateType, VariateTag>(lazy) -> mean_of_variates<VariateType, VariateTag>
+template<typename VariateType, typename VariateTag>
+struct as_feature<tag::mean_of_variates<VariateType, VariateTag>(lazy)>
+{
+    typedef tag::mean_of_variates<VariateType, VariateTag> type;
+};
+
+// mean_of_variates<VariateType, VariateTag>(immediate) -> immediate_mean_of_variates<VariateType, VariateTag>
+template<typename VariateType, typename VariateTag>
+struct as_feature<tag::mean_of_variates<VariateType, VariateTag>(immediate)>
+{
+    typedef tag::immediate_mean_of_variates<VariateType, VariateTag> type;
+};
+
+// for the purposes of feature-based dependency resolution,
+// immediate_mean provides the same feature as mean
+template<>
+struct feature_of<tag::immediate_mean>
+  : feature_of<tag::mean>
+{
+};
+
+// for the purposes of feature-based dependency resolution,
+// immediate_mean provides the same feature as mean
+template<>
+struct feature_of<tag::immediate_mean_of_weights>
+  : feature_of<tag::mean_of_weights>
+{
+};
+
+// for the purposes of feature-based dependency resolution,
+// immediate_mean provides the same feature as mean
+template<typename VariateType, typename VariateTag>
+struct feature_of<tag::immediate_mean_of_variates<VariateType, VariateTag> >
+  : feature_of<tag::mean_of_variates<VariateType, VariateTag> >
+{
+};
+
+// So that mean can be automatically substituted with
+// weighted_mean when the weight parameter is non-void.
+template<>
+struct as_weighted_feature<tag::mean>
+{
+    typedef tag::weighted_mean type;
+};
+
+template<>
+struct feature_of<tag::weighted_mean>
+  : feature_of<tag::mean>
+{};
+
+// So that immediate_mean can be automatically substituted with
+// immediate_weighted_mean when the weight parameter is non-void.
+template<>
+struct as_weighted_feature<tag::immediate_mean>
+{
+    typedef tag::immediate_weighted_mean type;
+};
+
+template<>
+struct feature_of<tag::immediate_weighted_mean>
+  : feature_of<tag::immediate_mean>
+{};
+
+// So that mean_of_weights<> can be automatically substituted with
+// weighted_mean_of_variates<> when the weight parameter is non-void.
+template<typename VariateType, typename VariateTag>
+struct as_weighted_feature<tag::mean_of_variates<VariateType, VariateTag> >
+{
+    typedef tag::weighted_mean_of_variates<VariateType, VariateTag> type;
+};
+
+template<typename VariateType, typename VariateTag>
+struct feature_of<tag::weighted_mean_of_variates<VariateType, VariateTag> >
+  : feature_of<tag::mean_of_variates<VariateType, VariateTag> >
+{
+};
+
+// So that immediate_mean_of_weights<> can be automatically substituted with
+// immediate_weighted_mean_of_variates<> when the weight parameter is non-void.
+template<typename VariateType, typename VariateTag>
+struct as_weighted_feature<tag::immediate_mean_of_variates<VariateType, VariateTag> >
+{
+    typedef tag::immediate_weighted_mean_of_variates<VariateType, VariateTag> type;
+};
+
+template<typename VariateType, typename VariateTag>
+struct feature_of<tag::immediate_weighted_mean_of_variates<VariateType, VariateTag> >
+  : feature_of<tag::immediate_mean_of_variates<VariateType, VariateTag> >
+{
+};
+
+////////////////////////////////////////////////////////////////////////////
+//// droppable_accumulator<mean_impl>
+////  need to specialize droppable lazy mean to cache the result at the
+////  point the accumulator is dropped.
+///// INTERNAL ONLY
+/////
+//template<typename Sample, typename SumFeature>
+//struct droppable_accumulator<impl::mean_impl<Sample, SumFeature> >
+//  : droppable_accumulator_base<
+//        with_cached_result<impl::mean_impl<Sample, SumFeature> >
+//    >
+//{
+//    template<typename Args>
+//    droppable_accumulator(Args const &args)
+//      : droppable_accumulator_base<
+//            with_cached_result<impl::mean_impl<Sample, SumFeature> >
+//        >(args)
+//    {
+//    }
+//};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/median.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/median.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,297 @@
+///////////////////////////////////////////////////////////////////////////////
+// median.hpp
+//
+//  Copyright 2006 Eric Niebler, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_MEDIAN_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_MEDIAN_HPP_EAN_28_10_2005
+
+#include <boost/mpl/placeholders.hpp>
+#include <boost/range/iterator_range.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/p_square_quantile.hpp>
+#include <boost/accumulators/statistics/density.hpp>
+#include <boost/accumulators/statistics/p_square_cumulative_distribution.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // median_impl
+    //
+    /**
+        @brief Median estimation based on the \f$P^2\f$ quantile estimator
+        
+        The \f$P^2\f$ algorithm is invoked with a quantile probability of 0.5.
+    */
+    template<typename Sample>
+    struct median_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type result_type;
+        
+        median_impl(dont_care) {}
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return p_square_quantile_for_median(args);
+        }
+    };
+    ///////////////////////////////////////////////////////////////////////////////
+    // with_density_median_impl
+    //
+    /**
+        @brief Median estimation based on the density estimator
+        
+        The algorithm determines the bin in which the \f$0.5*cnt\f$-th sample lies, \f$cnt\f$ being 
+        the total number of samples. It returns the approximate horizontal position of this sample, 
+        based on a linear interpolation inside the bin.
+    */
+    template<typename Sample>
+    struct with_density_median_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        typedef std::vector<std::pair<float_type, float_type> > histogram_type;
+        typedef iterator_range<typename histogram_type::iterator> range_type;
+        // for boost::result_of
+        typedef float_type result_type;
+                
+        template<typename Args>
+        with_density_median_impl(Args const &args)
+          : sum(numeric::average(args[sample | Sample()], (std::size_t)1))
+          , is_dirty(true)
+        {
+        }
+
+        void operator ()(dont_care)
+        {
+            this->is_dirty = true;
+        }
+
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            if (this->is_dirty)
+            {
+                this->is_dirty = false;
+            
+                std::size_t cnt = count(args);
+                range_type histogram = density(args);
+                typename range_type::iterator it = histogram.begin();
+                while (this->sum < 0.5 * cnt)
+                {
+                    this->sum += it->second * cnt;
+                    ++it;
+                }
+                --it;
+                float_type over = numeric::average(this->sum - 0.5 * cnt, it->second * cnt);
+                this->median = it->first * over + (it + 1)->first * (1. - over);
+            }
+            
+            return this->median;
+        }
+
+    private:
+        mutable float_type sum;
+        mutable bool is_dirty;
+        mutable float_type median;
+    };
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // with_p_square_cumulative_distribution_median_impl
+    //
+    /**
+        @brief Median estimation based on the \f$P^2\f$ cumulative distribution estimator
+        
+        The algorithm determines the first (leftmost) bin with a height exceeding 0.5. It 
+        returns the approximate horizontal position of where the cumulative distribution 
+        equals 0.5, based on a linear interpolation inside the bin.
+    */
+    template<typename Sample>
+    struct with_p_square_cumulative_distribution_median_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        typedef std::vector<std::pair<float_type, float_type> > histogram_type;
+        typedef iterator_range<typename histogram_type::iterator> range_type;
+        // for boost::result_of
+        typedef float_type result_type;
+                
+        with_p_square_cumulative_distribution_median_impl(dont_care)
+          : is_dirty(true)
+        {
+        }
+
+        void operator ()(dont_care)
+        {
+            this->is_dirty = true;
+        }
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            if (this->is_dirty)
+            {
+                this->is_dirty = false;
+            
+                range_type histogram = p_square_cumulative_distribution(args);
+                typename range_type::iterator it = histogram.begin();
+                while (it->second < 0.5)
+                {
+                    ++it;
+                }
+                float_type over = numeric::average(it->second - 0.5, it->second - (it - 1)->second);
+                this->median = it->first * over + (it + 1)->first * ( 1. - over );
+            }
+            
+            return this->median;
+        }
+    private:
+        
+        mutable bool is_dirty;
+        mutable float_type median;
+    };
+    
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::median
+// tag::with_densisty_median
+// tag::with_p_square_cumulative_distribution_median
+//
+namespace tag
+{
+    struct median
+      : depends_on<p_square_quantile_for_median>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::median_impl<mpl::_1> impl;
+    };
+    struct with_density_median
+      : depends_on<count, density>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::with_density_median_impl<mpl::_1> impl;
+    };
+    struct with_p_square_cumulative_distribution_median
+      : depends_on<p_square_cumulative_distribution>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::with_p_square_cumulative_distribution_median_impl<mpl::_1> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::median
+// extract::with_density_median
+// extract::with_p_square_cumulative_distribution_median
+//
+namespace extract
+{
+    extractor<tag::median> const median = {};
+    extractor<tag::with_density_median> const with_density_median = {};
+    extractor<tag::with_p_square_cumulative_distribution_median> const with_p_square_cumulative_distribution_median = {};
+}
+
+using extract::median;
+using extract::with_density_median;
+using extract::with_p_square_cumulative_distribution_median;
+
+// median(with_p_square_quantile) -> median
+template<>
+struct as_feature<tag::median(with_p_square_quantile)>
+{
+    typedef tag::median type;
+};
+
+// median(with_density) -> with_density_median
+template<>
+struct as_feature<tag::median(with_density)>
+{
+    typedef tag::with_density_median type;
+};
+
+// median(with_p_square_cumulative_distribution) -> with_p_square_cumulative_distribution_median
+template<>
+struct as_feature<tag::median(with_p_square_cumulative_distribution)>
+{
+    typedef tag::with_p_square_cumulative_distribution_median type;
+};
+
+// for the purposes of feature-based dependency resolution, 
+// with_density_median and with_p_square_cumulative_distribution_median 
+// provide the same feature as median
+template<>
+struct feature_of<tag::with_density_median>
+  : feature_of<tag::median>
+{
+};
+
+template<>
+struct feature_of<tag::with_p_square_cumulative_distribution_median>
+  : feature_of<tag::median>
+{
+};
+
+// So that median can be automatically substituted with
+// weighted_median when the weight parameter is non-void.
+template<>
+struct as_weighted_feature<tag::median>
+{
+    typedef tag::weighted_median type;
+};
+
+template<>
+struct feature_of<tag::weighted_median>
+  : feature_of<tag::median>
+{
+};
+
+// So that with_density_median can be automatically substituted with
+// with_density_weighted_median when the weight parameter is non-void.
+template<>
+struct as_weighted_feature<tag::with_density_median>
+{
+    typedef tag::with_density_weighted_median type;
+};
+
+template<>
+struct feature_of<tag::with_density_weighted_median>
+  : feature_of<tag::with_density_median>
+{
+};
+
+// So that with_p_square_cumulative_distribution_median can be automatically substituted with
+// with_p_square_cumulative_distribution_weighted_median when the weight parameter is non-void.
+template<>
+struct as_weighted_feature<tag::with_p_square_cumulative_distribution_median>
+{
+    typedef tag::with_p_square_cumulative_distribution_weighted_median type;
+};
+
+template<>
+struct feature_of<tag::with_p_square_cumulative_distribution_weighted_median>
+  : feature_of<tag::with_p_square_cumulative_distribution_median>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/min.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/min.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,83 @@
+///////////////////////////////////////////////////////////////////////////////
+// min.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_MIN_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_MIN_HPP_EAN_28_10_2005
+
+#include <limits>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // min_impl
+    template<typename Sample>
+    struct min_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef Sample result_type;
+
+        template<typename Args>
+        min_impl(Args const &args)
+          : min_(numeric::as_max(args[sample | Sample()]))
+        {
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            numeric::min_assign(this->min_, args[sample]);
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->min_;
+        }
+
+    private:
+        Sample min_;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::min
+//
+namespace tag
+{
+    struct min
+      : depends_on<>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::min_impl<mpl::_1> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::min
+//
+namespace extract
+{
+    extractor<tag::min> const min = {};
+}
+
+using extract::min;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/moment.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/moment.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,124 @@
+///////////////////////////////////////////////////////////////////////////////
+// moment.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_MOMENT_HPP_EAN_15_11_2005
+#define BOOST_ACCUMULATORS_STATISTICS_MOMENT_HPP_EAN_15_11_2005
+
+#include <cmath>
+#include <boost/mpl/int.hpp>
+#include <boost/mpl/assert.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+
+namespace boost { namespace numeric
+{
+    /// INTERNAL ONLY
+    ///
+    template<typename T>
+    T const &pow(T const &x, mpl::int_<1>)
+    {
+        return x;
+    }
+
+    /// INTERNAL ONLY
+    ///
+    template<typename T, int N>
+    T pow(T const &x, mpl::int_<N>)
+    {
+        T y = numeric::pow(x, mpl::int_<N/2>());
+        T z = y * y;
+        return (N % 2) ? (z * x) : z;
+    }
+}}
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // moment_impl
+    template<typename N, typename Sample>
+    struct moment_impl
+      : accumulator_base // TODO: also depends_on sum of powers
+    {
+        BOOST_MPL_ASSERT_RELATION(N::value, >, 0);
+        // for boost::result_of
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type result_type;
+
+        template<typename Args>
+        moment_impl(Args const &args)
+          : sum(args[sample | Sample()])
+        {
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            this->sum += numeric::pow(args[sample], N());
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return numeric::average(this->sum, count(args));
+        }
+
+    private:
+        Sample sum;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::moment
+//
+namespace tag
+{
+    template<int N>
+    struct moment
+      : depends_on<count>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::moment_impl<mpl::int_<N>, mpl::_1> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::moment
+//
+namespace extract
+{
+    BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, moment, (int))
+}
+
+using extract::moment;
+
+// So that moment<N> can be automatically substituted with 
+// weighted_moment<N> when the weight parameter is non-void
+template<int N>
+struct as_weighted_feature<tag::moment<N> >
+{
+    typedef tag::weighted_moment<N> type;
+};
+
+template<int N>
+struct feature_of<tag::weighted_moment<N> >
+  : feature_of<tag::moment<N> >
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/p_square_cumulative_distribution.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/p_square_cumulative_distribution.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,258 @@
+///////////////////////////////////////////////////////////////////////////////
+// p_square_cumulative_distribution.hpp
+//
+//  Copyright 2005 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_P_SQUARE_CUMULATIVE_DISTRIBUTION_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_P_SQUARE_CUMULATIVE_DISTRIBUTION_HPP_DE_01_01_2006
+
+#include <vector>
+#include <functional>
+#include <boost/parameter/keyword.hpp>
+#include <boost/range.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+
+namespace boost { namespace accumulators
+{
+///////////////////////////////////////////////////////////////////////////////
+// num_cells named parameter
+//
+BOOST_PARAMETER_NESTED_KEYWORD(tag, p_square_cumulative_distribution_num_cells, num_cells)
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // p_square_cumulative_distribution_impl
+    //  cumulative_distribution calculation (as histogram)
+    /**
+        @brief Histogram calculation of the cumulative distribution with the \f$P^2\f$ algorithm
+
+        A histogram of the sample cumulative distribution is computed dynamically without storing samples 
+        based on the \f$ P^2 \f$ algorithm. The returned histogram has a specifiable amount (num_cells) 
+        equiprobable (and not equal-sized) cells.
+
+        For further details, see
+        
+        R. Jain and I. Chlamtac, The P^2 algorithmus for dynamic calculation of quantiles and 
+        histograms without storing observations, Communications of the ACM,   
+        Volume 28 (October), Number 10, 1985, p. 1076-1085.
+
+        @param p_square_cumulative_distribution_num_cells. 
+    */
+    template<typename Sample>
+    struct p_square_cumulative_distribution_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        typedef std::vector<float_type> array_type;
+        typedef std::vector<std::pair<float_type, float_type> > histogram_type;
+        // for boost::result_of
+        typedef iterator_range<typename histogram_type::iterator> result_type;
+                
+        template<typename Args>
+        p_square_cumulative_distribution_impl(Args const &args)
+          : num_cells(args[p_square_cumulative_distribution_num_cells])
+          , heights(num_cells + 1)
+          , actual_positions(num_cells + 1)
+          , desired_positions(num_cells + 1)
+          , positions_increments(num_cells + 1)
+          , histogram(num_cells + 1)
+          , is_dirty(true)
+        {
+            std::size_t b = this->num_cells;
+            
+            for (std::size_t i = 0; i < b + 1; ++i)
+            {
+                this->actual_positions[i] = i + 1.;
+                this->desired_positions[i] = i + 1.;
+                this->positions_increments[i] = numeric::average(i, b);
+            }       
+        }
+        
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            this->is_dirty = true;
+        
+            std::size_t cnt = count(args);
+            std::size_t sample_cell = 1; // k
+            std::size_t b = this->num_cells;
+
+            // accumulate num_cells + 1 first samples
+            if (cnt <= b + 1)
+            {
+                this->heights[cnt - 1] = args[sample];
+                
+                // complete the initialization of heights by sorting
+                if (cnt == b + 1)
+                {
+                    std::sort(this->heights.begin(), this->heights.end());
+                }
+            }     
+            else
+            {
+                // find cell k such that heights[k-1] <= args[sample] < heights[k] and adjust extreme values
+                if (args[sample] < this->heights[0])
+                {
+                    this->heights[0] = args[sample];
+                    sample_cell = 1;
+                }
+                else if (this->heights[b] <= args[sample])
+                {
+                    this->heights[b] = args[sample];
+                    sample_cell = b;
+                }
+                else
+                {
+                    typename array_type::iterator it;
+                    it = std::upper_bound(
+                        this->heights.begin()
+                      , this->heights.end()
+                      , args[sample]
+                    );
+                                    
+                    sample_cell = std::distance(this->heights.begin(), it);
+                }
+                
+                // increment positions of markers above sample_cell
+                for (std::size_t i = sample_cell; i < b + 1; ++i)
+                {
+                    ++this->actual_positions[i];
+                }
+                
+                // update desired position of markers 2 to num_cells + 1
+                // (desired position of first marker is always 1)
+                for (std::size_t i = 1; i < b + 1; ++i)
+                {
+                    this->desired_positions[i] += this->positions_increments[i];
+                }
+                
+                // adjust heights of markers 2 to num_cells if necessary
+                for (std::size_t i = 1; i < b; ++i)
+                {
+                    // offset to desire position
+                    float_type d = this->desired_positions[i] - this->actual_positions[i];
+                                        
+                    // offset to next position
+                    float_type dp = this->actual_positions[i + 1] - this->actual_positions[i];
+                    
+                    // offset to previous position
+                    float_type dm = this->actual_positions[i - 1] - this->actual_positions[i];
+                    
+                    // height ds
+                    float_type hp = (this->heights[i + 1] - this->heights[i]) / dp;
+                    float_type hm = (this->heights[i - 1] - this->heights[i]) / dm;
+                    
+                    if ( ( d >= 1. && dp > 1. ) || ( d <= -1. && dm < -1. ) )
+                    {
+                        short sign_d = static_cast<short>(d / std::abs(d));
+                                               
+                        // try adjusting heights[i] using p-squared formula
+                        float_type h = this->heights[i] + sign_d / (dp - dm) * ( (sign_d - dm) * hp + (dp - sign_d) * hm );
+                        
+                        if ( this->heights[i - 1] < h && h < this->heights[i + 1] )
+                        {
+                            this->heights[i] = h;
+                        }
+                        else
+                        {
+                            // use linear formula
+                            if (d>0)
+                            {
+                                this->heights[i] += hp;
+                            }
+                            if (d<0)
+                            {
+                                this->heights[i] -= hm;
+                            }
+                        }
+                        this->actual_positions[i] += sign_d;
+                    }
+                }
+            }
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        { 
+            if (this->is_dirty)
+            {
+                this->is_dirty = false;
+            
+                // creates a vector of std::pair where each pair i holds
+                // the values heights[i] (x-axis of histogram) and
+                // actual_positions[i] / cnt (y-axis of histogram)
+    
+                std::size_t cnt = count(args);
+                
+                for (std::size_t i = 0; i < this->histogram.size(); ++i)
+                {
+                    this->histogram[i] = std::make_pair(this->heights[i], numeric::average(this->actual_positions[i], cnt));
+                }
+            }
+            //return histogram;
+            return make_iterator_range(this->histogram);
+        }
+
+    private:
+        std::size_t num_cells;            // number of cells b
+        array_type  heights;              // q_i
+        array_type  actual_positions;     // n_i
+        array_type  desired_positions;    // n'_i
+        array_type  positions_increments; // dn'_i
+        mutable histogram_type histogram; // histogram
+        mutable bool is_dirty;
+    };
+
+} // namespace detail
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::p_square_cumulative_distribution
+//
+namespace tag
+{
+    struct p_square_cumulative_distribution
+      : depends_on<count>
+      , p_square_cumulative_distribution_num_cells
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::p_square_cumulative_distribution_impl<mpl::_1> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::p_square_cumulative_distribution
+//
+namespace extract
+{
+    extractor<tag::p_square_cumulative_distribution> const p_square_cumulative_distribution = {};
+}
+
+using extract::p_square_cumulative_distribution;
+
+// So that p_square_cumulative_distribution can be automatically substituted with 
+// weighted_p_square_cumulative_distribution when the weight parameter is non-void
+template<>
+struct as_weighted_feature<tag::p_square_cumulative_distribution>
+{
+    typedef tag::weighted_p_square_cumulative_distribution type;
+};
+
+template<>
+struct feature_of<tag::weighted_p_square_cumulative_distribution>
+  : feature_of<tag::p_square_cumulative_distribution>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/p_square_quantile.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/p_square_quantile.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,254 @@
+///////////////////////////////////////////////////////////////////////////////
+// p_square_quantile.hpp
+//
+//  Copyright 2005 Daniel Egloff. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_P_SQUARE_QUANTILE_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_P_SQUARE_QUANTILE_HPP_DE_01_01_2006
+
+#include <functional>
+#include <boost/array.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // p_square_quantile_impl
+    //  single quantile estimation
+    /**
+        @brief Single quantile estimation with the \f$P^2\f$ algorithm
+
+        The \f$P^2\f$ algorithm estimates a quantile dynamically without storing samples. Instead of
+        storing the whole sample cumulative distribution, only five points (markers) are stored. The heights 
+        of these markers are the minimum and the maximum of the samples and the current estimates of the 
+        \f$(p/2)\f$-, \f$p\f$- and \f$(1+p)/2\f$-quantiles. Their positions are equal to the number 
+        of samples that are smaller or equal to the markers. Each time a new samples is recorded, the 
+        positions of the markers are updated and if necessary their heights are adjusted using a piecewise-
+        parabolic formula.
+
+        For further details, see
+
+        R. Jain and I. Chlamtac, The P^2 algorithmus fordynamic calculation of quantiles and
+        histograms without storing observations, Communications of the ACM,
+        Volume 28 (October), Number 10, 1985, p. 1076-1085.
+
+        @param quantile_probability
+    */
+    template<typename Sample, typename Impl>
+    struct p_square_quantile_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        typedef array<float_type, 5> array_type;
+        // for boost::result_of
+        typedef float_type result_type;
+
+        template<typename Args>
+        p_square_quantile_impl(Args const &args)
+          : p(is_same<Impl, for_median>::value ? 0.5 : args[quantile_probability | 0.5])
+          , heights()
+          , actual_positions()
+          , desired_positions()
+          , positions_increments()
+        {
+            for(std::size_t i = 0; i < 5; ++i)
+            {
+                this->actual_positions[i] = i + 1;
+            }
+
+            this->desired_positions[0] = 1.;
+            this->desired_positions[1] = 1. + 2. * this->p;
+            this->desired_positions[2] = 1. + 4. * this->p;
+            this->desired_positions[3] = 3. + 2. * this->p;
+            this->desired_positions[4] = 5.;
+            
+            this->positions_increments[0] = 0.;
+            this->positions_increments[1] = this->p / 2.;
+            this->positions_increments[2] = this->p;
+            this->positions_increments[3] = (1. + this->p) / 2.;
+            this->positions_increments[4] = 1.;
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            std::size_t cnt = count(args);
+
+            // accumulate 5 first samples
+            if(cnt <= 5)
+            {
+                this->heights[cnt - 1] = args[sample];
+
+                // complete the initialization of heights by sorting
+                if(cnt == 5)
+                {
+                    std::sort(this->heights.begin(), this->heights.end());
+                }
+            }
+            else
+            {
+                std::size_t sample_cell = 1; // k
+                
+                // find cell k such that heights[k-1] <= args[sample] < heights[k] and ajust extreme values
+                if (args[sample] < this->heights[0])
+                {
+                    this->heights[0] = args[sample];
+                    sample_cell = 1;
+                }
+                else if (this->heights[4] <= args[sample])
+                {
+                    this->heights[4] = args[sample];
+                    sample_cell = 4;
+                }
+                else
+                {
+                    typedef typename array_type::iterator iterator;
+                    iterator it = std::upper_bound(
+                        this->heights.begin()
+                      , this->heights.end()
+                      , args[sample]
+                    );
+
+                    sample_cell = std::distance(this->heights.begin(), it);
+                }
+
+                // update positions of markers above sample_cell
+                for(std::size_t i = sample_cell; i < 5; ++i)
+                {
+                    ++this->actual_positions[i];
+                }
+
+                // update desired positions of all markers
+                for(std::size_t i = 0; i < 5; ++i)
+                {
+                    this->desired_positions[i] += this->positions_increments[i];
+                }
+
+                // adjust heights and actual positions of markers 1 to 3 if necessary
+                for(std::size_t i = 1; i <= 3; ++i)
+                {
+                    // offset to desired positions
+                    float_type d = this->desired_positions[i] - this->actual_positions[i];
+
+                    // offset to next position
+                    float_type dp = this->actual_positions[i + 1] - this->actual_positions[i];
+
+                    // offset to previous position
+                    float_type dm = this->actual_positions[i - 1] - this->actual_positions[i];
+
+                    // height ds
+                    float_type hp = (this->heights[i + 1] - this->heights[i]) / dp;
+                    float_type hm = (this->heights[i - 1] - this->heights[i]) / dm;
+
+                    if((d >= 1. && dp > 1.) || (d <= -1. && dm < -1.))
+                    {
+                        short sign_d = static_cast<short>(d / std::abs(d));
+
+                        // try adjusting heights[i] using p-squared formula
+                        float_type h = this->heights[i] + sign_d / (dp - dm) * ((sign_d - dm) * hp
+                                     + (dp - sign_d) * hm);
+
+                        if(this->heights[i - 1] < h && h < this->heights[i + 1])
+                        {
+                            this->heights[i] = h;
+                        }
+                        else
+                        {
+                            // use linear formula
+                            if(d > 0)
+                            {
+                                this->heights[i] += hp;
+                            }
+                            if(d < 0)
+                            {
+                                this->heights[i] -= hm;
+                            }
+                        }
+                        this->actual_positions[i] += sign_d;
+                    }
+                }
+            }
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return this->heights[2];
+        }
+
+    private:
+        float_type p;                    // the quantile probability p
+        array_type heights;              // q_i
+        array_type actual_positions;     // n_i
+        array_type desired_positions;    // n'_i
+        array_type positions_increments; // dn'_i
+    };
+
+} // namespace detail
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::p_square_quantile
+//
+namespace tag
+{
+    struct p_square_quantile
+      : depends_on<count>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::p_square_quantile_impl<mpl::_1, regular> impl;
+    };
+    struct p_square_quantile_for_median
+      : depends_on<count>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::p_square_quantile_impl<mpl::_1, for_median> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::p_square_quantile
+// extract::p_square_quantile_for_median
+// 
+namespace extract
+{
+    extractor<tag::p_square_quantile> const p_square_quantile = {};
+    extractor<tag::p_square_quantile_for_median> const p_square_quantile_for_median = {};
+}
+
+using extract::p_square_quantile;
+using extract::p_square_quantile_for_median;
+
+// So that p_square_quantile can be automatically substituted with 
+// weighted_p_square_quantile when the weight parameter is non-void
+template<>
+struct as_weighted_feature<tag::p_square_quantile>
+{
+    typedef tag::weighted_p_square_quantile type;
+};
+
+template<>
+struct feature_of<tag::weighted_p_square_quantile>
+  : feature_of<tag::p_square_quantile>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/parameters/quantile_probability.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/parameters/quantile_probability.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,20 @@
+///////////////////////////////////////////////////////////////////////////////
+// quantile_probability.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_PARAMETERS_QUANTILE_PROBABILITY_HPP_EAN_03_11_2005
+#define BOOST_ACCUMULATORS_STATISTICS_PARAMETERS_QUANTILE_PROBABILITY_HPP_EAN_03_11_2005
+
+#include <boost/parameter/keyword.hpp>
+
+namespace boost { namespace accumulators
+{
+
+BOOST_PARAMETER_KEYWORD(tag, quantile_probability)
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/peaks_over_threshold.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/peaks_over_threshold.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,387 @@
+///////////////////////////////////////////////////////////////////////////////
+// peaks_over_threshold.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_PEAKS_OVER_THRESHOLD_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_PEAKS_OVER_THRESHOLD_HPP_DE_01_01_2006
+
+#include <vector>
+#include <limits>
+#include <numeric>
+#include <functional>
+#include <boost/range.hpp>
+#include <boost/mpl/if.hpp>
+#include <boost/mpl/int.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/tuple/tuple.hpp>
+#include <boost/lambda/lambda.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/tail.hpp>
+
+namespace boost { namespace accumulators
+{
+
+///////////////////////////////////////////////////////////////////////////////
+// threshold_probability and threshold named parameters
+//
+BOOST_PARAMETER_NESTED_KEYWORD(tag, pot_threshold_value, threshold_value)
+BOOST_PARAMETER_NESTED_KEYWORD(tag, pot_threshold_probability, threshold_probability)
+
+namespace impl
+{      
+    ///////////////////////////////////////////////////////////////////////////////
+    // peaks_over_threshold_impl
+    //  works with an explicit threshold value and does not depend on order statistics
+    /**
+        @brief Peaks over Threshold Method for Quantile and Tail Mean Estimation
+        
+        According to the theorem of Pickands-Balkema-de Haan, the distribution function \f$F_u(x)\f$ of 
+        the excesses \f$x\f$ over some sufficiently high threshold \f$u\f$ of a distribution function \f$F(x)\f$ 
+        may be approximated by a generalized Pareto distribution
+        \f[
+            G_{\xi,\beta}(x) =
+            \left\{
+            \begin{array}{ll}
+                \beta^{-1}\left(1+\frac{\xi x}{\beta}\right)^{-1/\xi-1} & \textrm{if }\xi\neq0\\
+                \beta^{-1}\exp\left(-\frac{x}{\beta}\right) & \textrm{if }\xi=0,    
+            \end{array}   
+            \right.
+        \f]
+        with suitable parameters \f$\xi\f$ and \f$\beta\f$ that can be estimated, e.g., with the method of moments, cf. 
+        Hosking and Wallis (1987),
+        \f[
+            \begin{array}{lll}
+            \hat{\xi} & = & \frac{1}{2}\left[1-\frac{(\hat{\mu}-u)^2}{\hat{\sigma}^2}\right]\\
+            \hat{\beta} & = & \frac{\hat{\mu}-u}{2}\left[\frac{(\hat{\mu}-u)^2}{\hat{\sigma}^2}+1\right],
+            \end{array}
+        \f]
+        \f$\hat{\mu}\f$ and \f$\hat{\sigma}^2\f$ being the empirical mean and variance of the samples over 
+        the threshold \f$u\f$. Equivalently, the distribution function 
+        \f$F_u(x-u)\f$ of the exceedances \f$x-u\f$ can be approximated by 
+        \f$G_{\xi,\beta}(x-u)=G_{\xi,\beta,u}(x)\f$. Since for \f$x\geq u\f$ the distribution function \f$F(x)\f$ 
+        can be written as
+        \f[
+            F(x) = [1 - \P(X \leq u)]F_u(x - u) + \P(X \leq u)
+        \f]
+        and the probability \f$\P(X \leq u)\f$ can be approximated by the empirical distribution function 
+        \f$F_n(u)\f$ evaluated at \f$u\f$, an estimator of \f$F(x)\f$ is given by 
+        \f[
+            \widehat{F}(x) = [1 - F_n(u)]G_{\xi,\beta,u}(x) + F_n(u).
+        \f]
+        It can be shown that \f$\widehat{F}(x)\f$ is a generalized 
+        Pareto distribution \f$G_{\xi,\bar{\beta},\bar{u}}(x)\f$ with \f$\bar{\beta}=\beta[1-F_n(u)]^{\xi}\f$ 
+        and \f$\bar{u}=u-\bar{\beta}\left\{[1-F_n(u)]^{-\xi}-1\right\}/\xi\f$. By inverting \f$\widehat{F}(x)\f$, 
+        one obtains an estimator for the \f$\alpha\f$-quantile,
+        \f[
+            \hat{q}_{\alpha} = \bar{u} + \frac{\bar{\beta}}{\xi}\left[(1-\alpha)^{-\xi}-1\right],
+        \f]
+        and similarly an estimator for the (coherent) tail mean,
+        \f[
+            \widehat{CTM}_{\alpha} = \hat{q}_{\alpha} - \frac{\bar{\beta}}{\xi-1}(1-\alpha)^{-\xi},
+        \f]
+        cf. McNeil and Frey (2000).
+        
+        Note that in case extreme values of the left tail are fitted, the distribution is mirrored with respect to the
+        \f$y\f$ axis such that the left tail can be treated as a right tail. The computed fit parameters thus define 
+        the Pareto distribution that fits the mirrored left tail. When quantities like a quantile or a tail mean are 
+        computed using the fit parameters obtained from the mirrored data, the result is mirrored back, yielding the 
+        correct result.
+        
+        For further details, see
+        
+        J. R. M. Hosking and J. R. Wallis, Parameter and quantile estimation for the generalized Pareto distribution, 
+        Technometrics, Volume 29, 1987, p. 339-349
+        
+        A. J. McNeil and R. Frey, Estimation of Tail-Related Risk Measures for Heteroscedastic Financial Time Series: 
+        an Extreme Value Approach, Journal of Empirical Finance, Volume 7, 2000, p. 271-300
+
+        @param quantile_probability
+        @param pot_threshold_value
+    */
+    template<typename Sample, typename LeftRight>
+    struct peaks_over_threshold_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        // for boost::result_of
+        typedef boost::tuple<float_type, float_type, float_type> result_type;
+        // for left tail fitting, mirror the extreme values
+        typedef mpl::int_<is_same<LeftRight, left>::value ? -1 : 1> sign;
+        
+        template<typename Args>
+        peaks_over_threshold_impl(Args const &args)
+          : Nu_(0)
+          , mu_(sign::value * numeric::average(args[sample | Sample()], (std::size_t)1))
+          , sigma2_(numeric::average(args[sample | Sample()], (std::size_t)1))
+          , threshold_(sign::value * args[pot_threshold_value])
+          , fit_parameters_(boost::make_tuple(0., 0., 0.))
+          , is_dirty_(true)
+        {
+        }
+        
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            this->is_dirty_ = true;
+        
+            if (sign::value * args[sample] > this->threshold_)
+            {
+                this->mu_ += args[sample];
+                this->sigma2_ += args[sample] * args[sample];
+                ++this->Nu_;
+            }
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            if (this->is_dirty_)
+            {
+                this->is_dirty_ = false;
+            
+                std::size_t cnt = count(args);
+                
+                this->mu_ = sign::value * numeric::average(this->mu_, this->Nu_);
+                this->sigma2_ = numeric::average(this->sigma2_, this->Nu_);
+                this->sigma2_ -= this->mu_ * this->mu_;
+                
+                float_type threshold_probability = numeric::average(cnt - this->Nu_, cnt);
+                
+                float_type tmp = numeric::average(( this->mu_ - this->threshold_ )*( this->mu_ - this->threshold_ ), this->sigma2_);
+                float_type xi_hat = 0.5 * ( 1. - tmp );
+                float_type beta_hat = 0.5 * ( this->mu_ - this->threshold_ ) * ( 1. + tmp );
+                float_type beta_bar = beta_hat * std::pow(1. - threshold_probability, xi_hat);
+                float_type u_bar = this->threshold_ - beta_bar * ( std::pow(1. - threshold_probability, -xi_hat) - 1.)/xi_hat;
+                this->fit_parameters_ = boost::make_tuple(u_bar, beta_bar, xi_hat);
+            }
+                      
+            return this->fit_parameters_;
+        }
+
+    private:
+        std::size_t Nu_;                     // number of samples larger than threshold
+        mutable float_type mu_;              // mean of Nu_ largest samples
+        mutable float_type sigma2_;          // variance of Nu_ largest samples
+        float_type threshold_;
+        mutable result_type fit_parameters_; // boost::tuple that stores fit parameters
+        mutable bool is_dirty_;
+    };
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // peaks_over_threshold_prob_impl
+    //  determines threshold from a given threshold probability using order statistics
+    /**
+        @brief Peaks over Threshold Method for Quantile and Tail Mean Estimation
+
+        @sa peaks_over_threshold_impl
+        
+        @param quantile_probability
+        @param pot_threshold_probability
+    */
+    template<typename Sample, typename LeftRight>
+    struct peaks_over_threshold_prob_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        // for boost::result_of
+        typedef boost::tuple<float_type, float_type, float_type> result_type;
+        // for left tail fitting, mirror the extreme values
+        typedef mpl::int_<is_same<LeftRight, left>::value ? -1 : 1> sign;
+        
+        template<typename Args>
+        peaks_over_threshold_prob_impl(Args const &args)
+          : mu_(sign::value * numeric::average(args[sample | Sample()], (std::size_t)1))
+          , sigma2_(numeric::average(args[sample | Sample()], (std::size_t)1))
+          , threshold_probability_(args[pot_threshold_probability])
+          , fit_parameters_(boost::make_tuple(0., 0., 0.))
+          , is_dirty_(true)
+        {
+        }
+        
+        void operator ()(dont_care)
+        {
+            this->is_dirty_ = true;
+        }
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            if (this->is_dirty_)
+            {            
+                this->is_dirty_ = false;
+             
+                std::size_t cnt = count(args);
+                
+                // the n'th cached sample provides an approximate threshold value u
+                std::size_t n = static_cast<std::size_t>(
+                    std::ceil(
+                        cnt * ( ( is_same<LeftRight, left>::value ) ? this->threshold_probability_ : 1. - this->threshold_probability_ )
+                    )
+                );
+                
+                // If n is in a valid range, return result, otherwise return NaN or throw exception
+                if ( n >= tail(args).size())
+                {
+                    if (std::numeric_limits<float_type>::has_quiet_NaN)
+                    {
+                        return boost::make_tuple(
+                            std::numeric_limits<float_type>::quiet_NaN()
+                          , std::numeric_limits<float_type>::quiet_NaN()
+                          , std::numeric_limits<float_type>::quiet_NaN()
+                        );
+                    }
+                    else
+                    {
+                        std::ostringstream msg;
+                        msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")";
+                        boost::throw_exception(std::runtime_error(msg.str()));
+                        return boost::make_tuple(Sample(0), Sample(0), Sample(0));
+                    }
+                }
+                else
+                {
+                    float_type u = *(tail(args).begin() + n - 1) * sign::value;
+    
+                    // compute mean and variance of samples above/under threshold value u
+                    for (std::size_t i = 0; i < n; ++i)
+                    {
+                        mu_ += *(tail(args).begin() + i);
+                        sigma2_ += *(tail(args).begin() + i) * (*(tail(args).begin() + i));
+                    }
+                    
+                    this->mu_ = sign::value * numeric::average(this->mu_, n);
+                    this->sigma2_ = numeric::average(this->sigma2_, n);
+                    this->sigma2_ -= this->mu_ * this->mu_;
+    
+                    if (is_same<LeftRight, left>::value)
+                        this->threshold_probability_ = 1. - this->threshold_probability_;
+                    
+                    float_type tmp = numeric::average(( this->mu_ - u )*( this->mu_ - u ), this->sigma2_);
+                    float_type xi_hat = 0.5 * ( 1. - tmp );
+                    float_type beta_hat = 0.5 * ( this->mu_ - u ) * ( 1. + tmp );
+                    float_type beta_bar = beta_hat * std::pow(1. - threshold_probability_, xi_hat);
+                    float_type u_bar = u - beta_bar * ( std::pow(1. - threshold_probability_, -xi_hat) - 1.)/xi_hat;
+                    this->fit_parameters_ = boost::make_tuple(u_bar, beta_bar, xi_hat);
+                }
+            }
+            
+            return this->fit_parameters_;
+        }
+
+    private:
+        mutable float_type mu_;                     // mean of samples above threshold u
+        mutable float_type sigma2_;                 // variance of samples above threshold u
+        mutable float_type threshold_probability_;
+        mutable result_type fit_parameters_;        // boost::tuple that stores fit parameters 
+        mutable bool is_dirty_;
+    };
+    
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::peaks_over_threshold
+//
+namespace tag
+{
+    template<typename LeftRight>
+    struct peaks_over_threshold
+      : depends_on<count>
+      , pot_threshold_value
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::peaks_over_threshold_impl<mpl::_1, LeftRight> impl;
+    };
+    
+    template<typename LeftRight>
+    struct peaks_over_threshold_prob
+      : depends_on<count, tail<LeftRight> >
+      , pot_threshold_probability
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::peaks_over_threshold_prob_impl<mpl::_1, LeftRight> impl;
+    };
+    
+    struct abstract_peaks_over_threshold
+      : depends_on<>
+    {
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::peaks_over_threshold
+//
+namespace extract
+{
+    extractor<tag::abstract_peaks_over_threshold> const peaks_over_threshold = {};
+}
+
+using extract::peaks_over_threshold;
+
+// peaks_over_threshold<LeftRight>(with_threshold_value) -> peaks_over_threshold<LeftRight>
+template<typename LeftRight>
+struct as_feature<tag::peaks_over_threshold<LeftRight>(with_threshold_value)>
+{
+    typedef tag::peaks_over_threshold<LeftRight> type;
+};
+
+// peaks_over_threshold<LeftRight>(with_threshold_probability) -> peaks_over_threshold_prob<LeftRight>
+template<typename LeftRight>
+struct as_feature<tag::peaks_over_threshold<LeftRight>(with_threshold_probability)>
+{
+    typedef tag::peaks_over_threshold_prob<LeftRight> type;
+};
+
+template<typename LeftRight>
+struct feature_of<tag::peaks_over_threshold<LeftRight> >
+  : feature_of<tag::abstract_peaks_over_threshold>
+{
+};
+
+template<typename LeftRight>
+struct feature_of<tag::peaks_over_threshold_prob<LeftRight> >
+  : feature_of<tag::abstract_peaks_over_threshold>
+{
+};
+
+// So that peaks_over_threshold can be automatically substituted 
+// with weighted_peaks_over_threshold when the weight parameter is non-void.
+template<typename LeftRight>
+struct as_weighted_feature<tag::peaks_over_threshold<LeftRight> >
+{
+    typedef tag::weighted_peaks_over_threshold<LeftRight> type;
+};
+
+template<typename LeftRight>
+struct feature_of<tag::weighted_peaks_over_threshold<LeftRight> >
+  : feature_of<tag::peaks_over_threshold<LeftRight> >
+{};
+
+// So that peaks_over_threshold_prob can be automatically substituted 
+// with weighted_peaks_over_threshold_prob when the weight parameter is non-void.
+template<typename LeftRight>
+struct as_weighted_feature<tag::peaks_over_threshold_prob<LeftRight> >
+{
+    typedef tag::weighted_peaks_over_threshold_prob<LeftRight> type;
+};
+
+template<typename LeftRight>
+struct feature_of<tag::weighted_peaks_over_threshold_prob<LeftRight> >
+  : feature_of<tag::peaks_over_threshold_prob<LeftRight> >
+{};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/pot_quantile.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/pot_quantile.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,206 @@
+///////////////////////////////////////////////////////////////////////////////
+// pot_quantile.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_POT_QUANTILE_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_POT_QUANTILE_HPP_DE_01_01_2006
+
+#include <vector>
+#include <limits>
+#include <numeric>
+#include <functional>
+#include <boost/parameter/keyword.hpp>
+#include <boost/tuple/tuple.hpp>
+#include <boost/mpl/if.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/lambda/lambda.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/tail.hpp>
+#include <boost/accumulators/statistics/peaks_over_threshold.hpp>
+#include <boost/accumulators/statistics/weighted_peaks_over_threshold.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // pot_quantile_impl
+    //  
+    /**
+        @brief Quantile Estimation based on Peaks over Threshold Method (for both left and right tails)
+        
+        Computes an estimate
+        \f[
+            \hat{q}_{\alpha} = \bar{u} + \frac{\bar{\beta}}{\xi}\left[(1-\alpha)^{-\xi}-1\right]
+        \f]
+        for a right or left extreme quantile, \f$\bar[u]\f$, \f$\bar{\beta}\f$ and \f$\xi\f$ being the parameters of the 
+        generalized Pareto distribution that approximates the right tail of the distribution (or the mirrored left tail, 
+        in case the left tail is used). In the latter case, the result is mirrored back, yielding the correct result.
+    */
+    template<typename Sample, typename Impl, typename LeftRight>
+    struct pot_quantile_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        // for boost::result_of
+        typedef float_type result_type;
+        
+        pot_quantile_impl(dont_care)
+         : sign_((is_same<LeftRight, left>::value) ? -1 : 1)
+        {
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            typedef
+                typename mpl::if_<
+                    is_same<Impl, weighted>
+                  , tag::weighted_peaks_over_threshold<LeftRight>
+                  , tag::peaks_over_threshold<LeftRight>
+                >::type
+            peaks_over_threshold_tag;
+
+            extractor<peaks_over_threshold_tag> const some_peaks_over_threshold = {};
+                
+            float_type u_bar    = some_peaks_over_threshold(args).get<0>();
+            float_type beta_bar = some_peaks_over_threshold(args).get<1>();
+            float_type xi_hat   = some_peaks_over_threshold(args).get<2>();
+                
+                return this->sign_*(u_bar + beta_bar/xi_hat * ( std::pow(
+                        is_same<LeftRight, left>::value ? args[quantile_probability] : 1. - args[quantile_probability]
+                    , -xi_hat
+                  ) - 1.));
+        }
+
+    private:
+        short sign_; // if the fit parameters from the mirrored left tail extreme values are used, mirror back the result
+    };
+    
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::pot_quantile<>
+// tag::pot_quantile_prob<>
+// tag::weighted_pot_quantile<>
+// tag::weighted_pot_quantile_prob<>
+//
+namespace tag
+{
+    template<typename LeftRight>
+    struct pot_quantile
+      : depends_on<peaks_over_threshold<LeftRight> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::pot_quantile_impl<mpl::_1, unweighted, LeftRight> impl;
+    };
+    template<typename LeftRight>
+    struct pot_quantile_prob
+      : depends_on<peaks_over_threshold_prob<LeftRight> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::pot_quantile_impl<mpl::_1, unweighted, LeftRight> impl;
+    };
+    template<typename LeftRight>
+    struct weighted_pot_quantile
+      : depends_on<weighted_peaks_over_threshold<LeftRight> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::pot_quantile_impl<mpl::_1, weighted, LeftRight> impl;
+    };
+    template<typename LeftRight>
+    struct weighted_pot_quantile_prob
+      : depends_on<weighted_peaks_over_threshold_prob<LeftRight> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::pot_quantile_impl<mpl::_1, weighted, LeftRight> impl;
+    };
+}
+
+// pot_quantile<LeftRight>(with_threshold_value) -> pot_quantile<LeftRight>
+template<typename LeftRight>
+struct as_feature<tag::pot_quantile<LeftRight>(with_threshold_value)>
+{
+    typedef tag::pot_quantile<LeftRight> type;
+};
+
+// pot_quantile<LeftRight>(with_threshold_probability) -> pot_quantile_prob<LeftRight>
+template<typename LeftRight>
+struct as_feature<tag::pot_quantile<LeftRight>(with_threshold_probability)>
+{
+    typedef tag::pot_quantile_prob<LeftRight> type;
+};
+
+// weighted_pot_quantile<LeftRight>(with_threshold_value) -> weighted_pot_quantile<LeftRight>
+template<typename LeftRight>
+struct as_feature<tag::weighted_pot_quantile<LeftRight>(with_threshold_value)>
+{
+    typedef tag::weighted_pot_quantile<LeftRight> type;
+};
+
+// weighted_pot_quantile<LeftRight>(with_threshold_probability) -> weighted_pot_quantile_prob<LeftRight>
+template<typename LeftRight>
+struct as_feature<tag::weighted_pot_quantile<LeftRight>(with_threshold_probability)>
+{
+    typedef tag::weighted_pot_quantile_prob<LeftRight> type;
+};
+
+// for the purposes of feature-based dependency resolution,
+// pot_quantile<LeftRight> and pot_quantile_prob<LeftRight> provide 
+// the same feature as quantile
+template<typename LeftRight>
+struct feature_of<tag::pot_quantile<LeftRight> >
+  : feature_of<tag::quantile>
+{
+};
+
+template<typename LeftRight>
+struct feature_of<tag::pot_quantile_prob<LeftRight> >
+  : feature_of<tag::quantile>
+{
+};
+
+// So that pot_quantile can be automatically substituted 
+// with weighted_pot_quantile when the weight parameter is non-void.
+template<typename LeftRight>
+struct as_weighted_feature<tag::pot_quantile<LeftRight> >
+{
+    typedef tag::weighted_pot_quantile<LeftRight> type;
+};
+
+template<typename LeftRight>
+struct feature_of<tag::weighted_pot_quantile<LeftRight> >
+  : feature_of<tag::pot_quantile<LeftRight> >
+{
+};
+
+// So that pot_quantile_prob can be automatically substituted 
+// with weighted_pot_quantile_prob when the weight parameter is non-void.
+template<typename LeftRight>
+struct as_weighted_feature<tag::pot_quantile_prob<LeftRight> >
+{
+    typedef tag::weighted_pot_quantile_prob<LeftRight> type;
+};
+
+template<typename LeftRight>
+struct feature_of<tag::weighted_pot_quantile_prob<LeftRight> >
+  : feature_of<tag::pot_quantile_prob<LeftRight> >
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/pot_tail_mean.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/pot_tail_mean.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,212 @@
+///////////////////////////////////////////////////////////////////////////////
+// pot_tail_mean.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_POT_TAIL_MEAN_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_POT_TAIL_MEAN_HPP_DE_01_01_2006
+
+#include <vector>
+#include <limits>
+#include <numeric>
+#include <functional>
+#include <boost/range.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/tuple/tuple.hpp>
+#include <boost/mpl/if.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/lambda/lambda.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/peaks_over_threshold.hpp>
+#include <boost/accumulators/statistics/weighted_peaks_over_threshold.hpp>
+#include <boost/accumulators/statistics/pot_quantile.hpp>
+#include <boost/accumulators/statistics/tail_mean.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // pot_tail_mean_impl
+    //  
+    /**
+        @brief Estimation of the (coherent) tail mean based on the peaks over threshold method (for both left and right tails)
+        
+        Computes an estimate for the (coherent) tail mean
+        \f[
+            \widehat{CTM}_{\alpha} = \hat{q}_{\alpha} - \frac{\bar{\beta}}{\xi-1}(1-\alpha)^{-\xi},
+        \f]
+        where \f$\bar[u]\f$, \f$\bar{\beta}\f$ and \f$\xi\f$ are the parameters of the 
+        generalized Pareto distribution that approximates the right tail of the distribution (or the 
+        mirrored left tail, in case the left tail is used). In the latter case, the result is mirrored 
+        back, yielding the correct result.
+    */
+    template<typename Sample, typename Impl, typename LeftRight>
+    struct pot_tail_mean_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        // for boost::result_of
+        typedef float_type result_type;
+        
+        pot_tail_mean_impl(dont_care)
+          : sign_((is_same<LeftRight, left>::value) ? -1 : 1)
+        {
+        }
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            typedef
+                typename mpl::if_<
+                    is_same<Impl, weighted>
+                  , tag::weighted_peaks_over_threshold<LeftRight>
+                  , tag::peaks_over_threshold<LeftRight>
+                >::type
+            peaks_over_threshold_tag;
+
+            typedef
+                typename mpl::if_<
+                    is_same<Impl, weighted>
+                  , tag::weighted_pot_quantile<LeftRight>
+                  , tag::pot_quantile<LeftRight>
+                >::type
+            pot_quantile_tag;
+
+            extractor<peaks_over_threshold_tag> const some_peaks_over_threshold = {};
+            extractor<pot_quantile_tag> const some_pot_quantile = {};
+        
+            float_type beta_bar = some_peaks_over_threshold(args).get<1>();
+            float_type xi_hat   = some_peaks_over_threshold(args).get<2>();
+            
+            return some_pot_quantile(args) - this->sign_ * beta_bar/( xi_hat - 1. ) * std::pow(
+                is_same<LeftRight, left>::value ? args[quantile_probability] : 1. - args[quantile_probability]
+              , -xi_hat);
+        }
+    private:
+        short sign_; // if the fit parameters from the mirrored left tail extreme values are used, mirror back the result
+    };
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::pot_tail_mean
+// tag::pot_tail_mean_prob
+//
+namespace tag
+{
+    template<typename LeftRight>
+    struct pot_tail_mean
+      : depends_on<peaks_over_threshold<LeftRight>, pot_quantile<LeftRight> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::pot_tail_mean_impl<mpl::_1, unweighted, LeftRight> impl;
+    };
+    template<typename LeftRight>
+    struct pot_tail_mean_prob
+      : depends_on<peaks_over_threshold_prob<LeftRight>, pot_quantile_prob<LeftRight> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::pot_tail_mean_impl<mpl::_1, unweighted, LeftRight> impl;
+    };
+    template<typename LeftRight>
+    struct weighted_pot_tail_mean
+      : depends_on<weighted_peaks_over_threshold<LeftRight>, weighted_pot_quantile<LeftRight> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::pot_tail_mean_impl<mpl::_1, weighted, LeftRight> impl;
+    };
+    template<typename LeftRight>
+    struct weighted_pot_tail_mean_prob
+      : depends_on<weighted_peaks_over_threshold_prob<LeftRight>, weighted_pot_quantile_prob<LeftRight> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::pot_tail_mean_impl<mpl::_1, weighted, LeftRight> impl;
+    };
+}
+
+// pot_tail_mean<LeftRight>(with_threshold_value) -> pot_tail_mean<LeftRight>
+template<typename LeftRight>
+struct as_feature<tag::pot_tail_mean<LeftRight>(with_threshold_value)>
+{
+    typedef tag::pot_tail_mean<LeftRight> type;
+};
+
+// pot_tail_mean<LeftRight>(with_threshold_probability) -> pot_tail_mean_prob<LeftRight>
+template<typename LeftRight>
+struct as_feature<tag::pot_tail_mean<LeftRight>(with_threshold_probability)>
+{
+    typedef tag::pot_tail_mean_prob<LeftRight> type;
+};
+
+// weighted_pot_tail_mean<LeftRight>(with_threshold_value) -> weighted_pot_tail_mean<LeftRight>
+template<typename LeftRight>
+struct as_feature<tag::weighted_pot_tail_mean<LeftRight>(with_threshold_value)>
+{
+    typedef tag::weighted_pot_tail_mean<LeftRight> type;
+};
+
+// weighted_pot_tail_mean<LeftRight>(with_threshold_probability) -> weighted_pot_tail_mean_prob<LeftRight>
+template<typename LeftRight>
+struct as_feature<tag::weighted_pot_tail_mean<LeftRight>(with_threshold_probability)>
+{
+    typedef tag::weighted_pot_tail_mean_prob<LeftRight> type;
+};
+
+// for the purposes of feature-based dependency resolution,
+// pot_tail_mean<LeftRight> and pot_tail_mean_prob<LeftRight> provide 
+// the same feature as tail_mean
+template<typename LeftRight>
+struct feature_of<tag::pot_tail_mean<LeftRight> >
+  : feature_of<tag::tail_mean>
+{
+};
+
+template<typename LeftRight>
+struct feature_of<tag::pot_tail_mean_prob<LeftRight> >
+  : feature_of<tag::tail_mean>
+{
+};
+
+// So that pot_tail_mean can be automatically substituted 
+// with weighted_pot_tail_mean when the weight parameter is non-void.
+template<typename LeftRight>
+struct as_weighted_feature<tag::pot_tail_mean<LeftRight> >
+{
+    typedef tag::weighted_pot_tail_mean<LeftRight> type;
+};
+
+template<typename LeftRight>
+struct feature_of<tag::weighted_pot_tail_mean<LeftRight> >
+  : feature_of<tag::pot_tail_mean<LeftRight> >
+{
+};
+
+// So that pot_tail_mean_prob can be automatically substituted 
+// with weighted_pot_tail_mean_prob when the weight parameter is non-void.
+template<typename LeftRight>
+struct as_weighted_feature<tag::pot_tail_mean_prob<LeftRight> >
+{
+    typedef tag::weighted_pot_tail_mean_prob<LeftRight> type;
+};
+
+template<typename LeftRight>
+struct feature_of<tag::weighted_pot_tail_mean_prob<LeftRight> >
+  : feature_of<tag::pot_tail_mean_prob<LeftRight> >
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/skewness.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/skewness.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,112 @@
+///////////////////////////////////////////////////////////////////////////////
+// skewness.hpp
+//
+//  Copyright 2006 Olivier Gygi, Daniel Egloff. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_SKEWNESS_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_SKEWNESS_HPP_EAN_28_10_2005
+
+#include <limits>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/moment.hpp>
+#include <boost/accumulators/statistics/mean.hpp>
+
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // skewness_impl
+    /**
+        @brief Skewness estimation
+        
+        The skewness of a sample distribution is defined as the ratio of the 3rd central moment and the \f$ 3/2 \f$-th power 
+        of the 2nd central moment (the variance) of the sampless 3. The skewness can also be expressed by the simple moments:
+        
+        \f[
+            \hat{g}_1 =
+                \frac
+                {\widehat{m}_n^{(3)}-3\widehat{m}_n^{(2)}\hat{\mu}_n+2\hat{\mu}_n^3}
+                {\left(\widehat{m}_n^{(2)} - \hat{\mu}_n^{2}\right)^{3/2}}
+        \f]
+        
+        where \f$ \widehat{m}_n^{(i)} \f$ are the \f$ i \f$-th moment and \f$ \hat{\mu}_n \f$ the mean (first moment) of the 
+        \f$ n \f$ samples.
+    */
+    template<typename Sample>
+    struct skewness_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef typename numeric::functional::average<Sample, Sample>::result_type result_type;
+
+        skewness_impl(dont_care)
+        {
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return numeric::average(
+                        moment<3>(args) 
+                        - 3. * moment<2>(args) * mean(args)
+                        + 2. * mean(args) * mean(args) * mean(args)
+                      , ( moment<2>(args) - mean(args) * mean(args) ) 
+                        * std::sqrt( moment<2>(args) - mean(args) * mean(args) )
+                   );
+        }
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::skewness
+//
+namespace tag
+{
+    struct skewness
+      : depends_on<mean, moment<2>, moment<3> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::skewness_impl<mpl::_1> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::skewness
+//
+namespace extract
+{
+    extractor<tag::skewness> const skewness = {};
+}
+
+using extract::skewness;
+
+// So that skewness can be automatically substituted with 
+// weighted_skewness when the weight parameter is non-void
+template<>
+struct as_weighted_feature<tag::skewness>
+{
+    typedef tag::weighted_skewness type;
+};
+
+template<>
+struct feature_of<tag::weighted_skewness>
+  : feature_of<tag::skewness>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/stats.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/stats.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,29 @@
+///////////////////////////////////////////////////////////////////////////////
+/// \file stats.hpp
+/// Contains the stats<> template.
+///
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_STATS_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_STATS_HPP_EAN_28_10_2005
+
+#include <boost/preprocessor/repetition/enum_params.hpp>
+#include <boost/mpl/vector.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+
+namespace boost { namespace accumulators
+{
+
+///////////////////////////////////////////////////////////////////////////////
+/// An MPL sequence of statistics.
+template<BOOST_PP_ENUM_PARAMS(BOOST_ACCUMULATORS_MAX_FEATURES, typename Stat)>
+struct stats
+  : mpl::vector<BOOST_PP_ENUM_PARAMS(BOOST_ACCUMULATORS_MAX_FEATURES, Stat)>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/sum.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/sum.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,137 @@
+///////////////////////////////////////////////////////////////////////////////
+// sum.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_SUM_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_SUM_HPP_EAN_28_10_2005
+
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/parameters/weight.hpp>
+#include <boost/accumulators/framework/accumulators/external_accumulator.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // sum_impl
+    template<typename Sample, typename Tag>
+    struct sum_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef Sample result_type;
+
+        template<typename Args>
+        sum_impl(Args const &args)
+          : sum(args[parameter::keyword<Tag>::get() | Sample()])
+        {
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            // what about overflow?
+            this->sum += args[parameter::keyword<Tag>::get()];
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->sum;
+        }
+
+    private:
+
+        Sample sum;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::sum
+// tag::sum_of_weights
+// tag::sum_of_variates
+//
+namespace tag
+{
+    struct sum
+      : depends_on<>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::sum_impl<mpl::_1, tag::sample> impl;
+    };
+
+    struct sum_of_weights
+      : depends_on<>
+    {
+        typedef mpl::true_ is_weight_accumulator;
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::sum_impl<mpl::_2, tag::weight> impl;
+    };
+    
+    template<typename VariateType, typename VariateTag>
+    struct sum_of_variates
+      : depends_on<>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef mpl::always<accumulators::impl::sum_impl<VariateType, VariateTag> > impl;
+    };
+    
+    struct abstract_sum_of_variates
+      : depends_on<>
+    {
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::sum
+// extract::sum_of_weights
+// extract::sum_of_variates
+//
+namespace extract
+{
+    extractor<tag::sum> const sum = {};
+    extractor<tag::sum_of_weights> const sum_of_weights = {};
+    extractor<tag::abstract_sum_of_variates> const sum_of_variates = {};
+}
+
+using extract::sum;
+using extract::sum_of_weights;
+using extract::sum_of_variates;
+
+// So that mean can be automatically substituted with
+// weighted_mean when the weight parameter is non-void.
+template<>
+struct as_weighted_feature<tag::sum>
+{
+    typedef tag::weighted_sum type;
+};
+
+template<>
+struct feature_of<tag::weighted_sum>
+  : feature_of<tag::sum>
+{};
+
+template<typename VariateType, typename VariateTag>
+struct feature_of<tag::sum_of_variates<VariateType, VariateTag> >
+  : feature_of<tag::abstract_sum_of_variates>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/tail.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/tail.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,328 @@
+///////////////////////////////////////////////////////////////////////////////
+// tail.hpp
+//
+//  Copyright 2005 Eric Niebler, Michael Gauckler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_TAIL_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_TAIL_HPP_EAN_28_10_2005
+
+#include <vector>
+#include <functional>
+#include <boost/range.hpp>
+#include <boost/mpl/if.hpp>
+#include <boost/mpl/or.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/iterator/reverse_iterator.hpp>
+#include <boost/iterator/permutation_iterator.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+
+namespace boost { namespace accumulators
+{
+///////////////////////////////////////////////////////////////////////////////
+// cache_size named parameters
+BOOST_PARAMETER_NESTED_KEYWORD(tag, right_tail_cache_size, cache_size)
+BOOST_PARAMETER_NESTED_KEYWORD(tag, left_tail_cache_size, cache_size)
+
+namespace detail
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // tail_range
+    /// INTERNAL ONLY
+    ///
+    template<typename ElementIterator, typename IndexIterator>
+    struct tail_range
+    {
+        typedef boost::iterator_range<
+            boost::reverse_iterator<boost::permutation_iterator<ElementIterator, IndexIterator> >
+        > type;
+    };
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // make_tail_range
+    /// INTERNAL ONLY
+    ///
+    template<typename ElementIterator, typename IndexIterator>
+    typename tail_range<ElementIterator, IndexIterator>::type
+    make_tail_range(ElementIterator elem_begin, IndexIterator index_begin, IndexIterator index_end)
+    {
+        return boost::make_iterator_range(
+            boost::make_reverse_iterator(
+                boost::make_permutation_iterator(elem_begin, index_end)
+            )
+          , boost::make_reverse_iterator(
+                boost::make_permutation_iterator(elem_begin, index_begin)
+            )
+        );
+    }
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // stat_assign_visitor
+    /// INTERNAL ONLY
+    ///
+    template<typename Args>
+    struct stat_assign_visitor
+    {
+        stat_assign_visitor(Args const &args, std::size_t index)
+          : args(args)
+          , index(index)
+        {
+        }
+
+        template<typename Stat>
+        void operator ()(Stat &stat) const
+        {
+            stat.assign(this->args, this->index);
+        }
+
+    private:
+        Args const &args;
+        std::size_t index;
+    };
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // stat_assign
+    /// INTERNAL ONLY
+    ///
+    template<typename Args>
+    inline stat_assign_visitor<Args> const stat_assign(Args const &args, std::size_t index)
+    {
+        return stat_assign_visitor<Args>(args, index);
+    }
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // is_tail_variate_feature
+    /// INTERNAL ONLY
+    ///
+    template<typename Stat, typename LeftRight>
+    struct is_tail_variate_feature
+      : mpl::false_
+    {
+    };
+
+    /// INTERNAL ONLY
+    ///
+    template<typename VariateType, typename VariateTag, typename LeftRight>
+    struct is_tail_variate_feature<tag::tail_variate<VariateType, VariateTag, LeftRight>, LeftRight>
+      : mpl::true_
+    {
+    };
+
+    /// INTERNAL ONLY
+    ///
+    template<typename LeftRight>
+    struct is_tail_variate_feature<tag::tail_weights<LeftRight>, LeftRight>
+      : mpl::true_
+    {
+    };
+    
+} // namespace detail
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // tail_impl
+    template<typename Sample, typename LeftRight>
+    struct tail_impl
+      : accumulator_base
+    {
+        // LeftRight must be either right or left
+        BOOST_MPL_ASSERT((
+            mpl::or_<is_same<LeftRight, right>, is_same<LeftRight, left> >
+        ));
+
+        typedef
+            typename mpl::if_<
+                is_same<LeftRight, right>
+              , numeric::functional::greater<Sample const, Sample const>
+              , numeric::functional::less<Sample const, Sample const>
+            >::type
+        predicate_type;
+
+        // for boost::result_of
+        typedef typename detail::tail_range<
+            typename std::vector<Sample>::const_iterator
+          , std::vector<std::size_t>::iterator
+        >::type result_type;
+
+        template<typename Args>
+        tail_impl(Args const &args)
+          : is_sorted(false)
+          , indices()
+          , samples(args[tag::tail<LeftRight>::cache_size], args[sample | Sample()])
+        {
+            this->indices.reserve(this->samples.size());
+        }
+
+        tail_impl(tail_impl const &that)
+          : is_sorted(that.is_sorted)
+          , indices(that.indices)
+          , samples(that.samples)
+        {
+            this->indices.reserve(that.indices.capacity());
+        }
+
+        // This just stores the heap and the samples.
+        // In operator()() below, if we are adding a new sample
+        // to the sample cache, we force all the 
+        // tail_variates to update also. (It's not
+        // good enough to wait for the accumulator_set to do it
+        // for us because then information about whether a sample
+        // was stored and where is lost, and would need to be
+        // queried at runtime, which would be slow.) This is
+        // implemented as a filtered visitation over the stats,
+        // which we can access because args[accumulator] gives us
+        // all the stats.
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            if(this->indices.size() < this->indices.capacity())
+            {
+                this->indices.push_back(this->indices.size());
+                this->assign(args, this->indices.back());
+            }
+            else if(predicate_type()(args[sample], this->samples[this->indices[0]]))
+            {
+                std::pop_heap(this->indices.begin(), this->indices.end(), indirect_cmp(this->samples));
+                this->assign(args, this->indices.back());
+            }
+        }
+
+        result_type result(dont_care) const
+        {
+            if(!this->is_sorted)
+            {
+                // Must use the same predicate here as in push_heap/pop_heap above.
+                std::sort_heap(this->indices.begin(), this->indices.end(), indirect_cmp(this->samples));
+                // sort_heap puts elements in reverse order. Calling std::reverse
+                // turns the sorted sequence back into a valid heap.
+                std::reverse(this->indices.begin(), this->indices.end());
+                this->is_sorted = true;
+            }
+
+            return detail::make_tail_range(
+                this->samples.begin()
+              , this->indices.begin()
+              , this->indices.end()
+            );
+        }
+
+    private:
+
+        struct is_tail_variate
+        {
+            template<typename T>
+            struct apply
+              : detail::is_tail_variate_feature<
+                    typename detail::feature_tag<T>::type
+                  , LeftRight
+                >
+            {};
+        };
+
+        template<typename Args>
+        void assign(Args const &args, std::size_t index)
+        {
+            this->samples[index] = args[sample];
+            std::push_heap(this->indices.begin(), this->indices.end(), indirect_cmp(this->samples));
+            this->is_sorted = false;
+            // Tell the tail variates to store their values also
+            args[accumulator].template visit_if<is_tail_variate>(detail::stat_assign(args, index));
+        }
+
+        ///////////////////////////////////////////////////////////////////////////////
+        // 
+        struct indirect_cmp
+          : std::binary_function<std::size_t, std::size_t, bool>
+        {
+            indirect_cmp(std::vector<Sample> const &samples)
+              : samples(samples)
+            {
+            }
+
+            bool operator ()(std::size_t left, std::size_t right) const
+            {
+                return predicate_type()(this->samples[left], this->samples[right]);
+            }
+
+        private:
+            std::vector<Sample> const &samples;
+        };
+
+        mutable bool is_sorted;
+        mutable std::vector<std::size_t> indices;
+        std::vector<Sample> samples;
+    };
+
+} // namespace impl
+
+// TODO The templatized tag::tail below should inherit from the correct named parameter.
+// The following lines provide a workaround, but there must be a better way of doing this.
+template<typename T>
+struct tail_cache_size_named_arg
+{
+};
+template<>
+struct tail_cache_size_named_arg<left>
+  : tag::left_tail_cache_size
+{
+};
+template<>
+struct tail_cache_size_named_arg<right>
+  : tag::right_tail_cache_size
+{
+};
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::tail<>
+//
+namespace tag
+{
+    template<typename LeftRight>
+    struct tail
+      : depends_on<>
+      , tail_cache_size_named_arg<LeftRight>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::tail_impl<mpl::_1, LeftRight> impl;
+
+        #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED
+        /// tag::tail<LeftRight>::cache_size named parameter
+        static boost::parameter::keyword<tail_cache_size_named_arg<LeftRight> > const cache_size;
+        #endif
+    };
+    
+    struct abstract_tail
+      : depends_on<>
+    {
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::tail
+//
+namespace extract
+{
+    extractor<tag::abstract_tail> const tail = {};
+}
+
+using extract::tail;
+
+template<typename LeftRight>
+struct feature_of<tag::tail<LeftRight> >
+  : feature_of<tag::abstract_tail>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/tail_mean.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/tail_mean.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,234 @@
+///////////////////////////////////////////////////////////////////////////////
+// tail_mean.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_TAIL_MEAN_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_TAIL_MEAN_HPP_DE_01_01_2006
+
+#include <numeric>
+#include <vector>
+#include <limits>
+#include <functional>
+#include <sstream>
+#include <stdexcept>
+#include <boost/throw_exception.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/tail.hpp>
+#include <boost/accumulators/statistics/tail_quantile.hpp>
+#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+     
+    ///////////////////////////////////////////////////////////////////////////////
+    // coherent_tail_mean_impl
+    //
+    /**
+        @brief Estimation of the coherent tail mean based on order statistics (for both left and right tails)
+
+        The coherent tail mean \f$\widehat{CTM}_{n,\alpha}(X)\f$ is equal to the non-coherent tail mean \f$\widehat{NCTM}_{n,\alpha}(X)\f$ 
+        plus a correction term that ensures coherence in case of non-continuous distributions.
+        
+        \f[
+            \widehat{CTM}_{n,\alpha}^{\mathrm{right}}(X) = \widehat{NCTM}_{n,\alpha}^{\mathrm{right}}(X) + 
+            \frac{1}{\lceil n(1-\alpha)\rceil}\hat{q}_{n,\alpha}(X)\left(1 - \alpha - \frac{1}{n}\lceil n(1-\alpha)\rceil \right)
+        \f]
+        
+        \f[
+            \widehat{CTM}_{n,\alpha}^{\mathrm{left}}(X) = \widehat{NCTM}_{n,\alpha}^{\mathrm{left}}(X) + 
+            \frac{1}{\lceil n\alpha\rceil}\hat{q}_{n,\alpha}(X)\left(\alpha - \frac{1}{n}\lceil n\alpha\rceil \right)
+        \f]
+    */
+    template<typename Sample, typename LeftRight>
+    struct coherent_tail_mean_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        // for boost::result_of
+        typedef float_type result_type;
+        
+        coherent_tail_mean_impl(dont_care) {}
+               
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            std::size_t cnt = count(args);
+        
+            std::size_t n = static_cast<std::size_t>(
+                std::ceil(
+                    cnt * ( ( is_same<LeftRight, left>::value ) ? args[quantile_probability] : 1. - args[quantile_probability] )
+                )
+            );
+            
+            extractor<tag::non_coherent_tail_mean<LeftRight> > const some_non_coherent_tail_mean = {};
+            
+            return some_non_coherent_tail_mean(args)
+                 + numeric::average(quantile(args), n)
+                 * (
+                     ( is_same<LeftRight, left>::value ) ? args[quantile_probability] : 1. - args[quantile_probability]
+                     - numeric::average(n, count(args))
+                   );
+        }
+    };
+    
+    ///////////////////////////////////////////////////////////////////////////////
+    // non_coherent_tail_mean_impl
+    //       
+    /**
+        @brief Estimation of the (non-coherent) tail mean based on order statistics (for both left and right tails)
+
+        An estimation of the non-coherent tail mean \f$\widehat{NCTM}_{n,\alpha}(X)\f$ is given by the mean of the 
+        \f$\lceil n\alpha\rceil\f$ smallest samples (left tail) or the mean of the  \f$\lceil n(1-\alpha)\rceil\f$ 
+        largest samples (right tail), \f$n\f$ being the total number of samples and \f$\alpha\f$ the quantile level:
+        
+        \f[
+            \widehat{NCTM}_{n,\alpha}^{\mathrm{right}}(X) = \frac{1}{\lceil n(1-\alpha)\rceil} \sum_{i=\lceil \alpha n \rceil}^n X_{i:n}
+        \f]
+        
+        \f[
+            \widehat{NCTM}_{n,\alpha}^{\mathrm{left}}(X) = \frac{1}{\lceil n\alpha\rceil} \sum_{i=1}^{\lceil \alpha n \rceil} X_{i:n}
+        \f]
+        
+        It thus requires the caching of at least the \f$\lceil n\alpha\rceil\f$ smallest or the \f$\lceil n(1-\alpha)\rceil\f$ 
+        largest samples.
+                
+        @param quantile_probability
+    */
+    template<typename Sample, typename LeftRight>
+    struct non_coherent_tail_mean_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        // for boost::result_of
+        typedef float_type result_type;
+        
+        non_coherent_tail_mean_impl(dont_care) {}
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            std::size_t cnt = count(args);
+        
+            std::size_t n = static_cast<std::size_t>(
+                std::ceil(
+                    cnt * ( ( is_same<LeftRight, left>::value ) ? args[quantile_probability] : 1. - args[quantile_probability] )
+                )
+            );
+            
+            // If n is in a valid range, return result, otherwise return NaN or throw exception
+            if (n <= tail(args).size())
+                return numeric::average(
+                    std::accumulate(
+                        tail(args).begin()
+                      , tail(args).begin() + n
+                      , Sample(0)
+                    )
+                  , n
+                );
+            else
+            {
+                if (std::numeric_limits<result_type>::has_quiet_NaN)
+                {
+                    return std::numeric_limits<result_type>::quiet_NaN();
+                }
+                else
+                {
+                    std::ostringstream msg;
+                    msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")";
+                    boost::throw_exception(std::runtime_error(msg.str()));
+                    return Sample(0);
+                }
+            }          
+        }
+    };
+
+} // namespace impl
+
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::coherent_tail_mean<>
+// tag::non_coherent_tail_mean<>
+//
+namespace tag
+{
+    template<typename LeftRight>
+    struct coherent_tail_mean
+      : depends_on<count, quantile, non_coherent_tail_mean<LeftRight> >
+    {
+        typedef accumulators::impl::coherent_tail_mean_impl<mpl::_1, LeftRight> impl;
+    };
+    
+    template<typename LeftRight>
+    struct non_coherent_tail_mean
+      : depends_on<count, tail<LeftRight> >
+    {
+        typedef accumulators::impl::non_coherent_tail_mean_impl<mpl::_1, LeftRight> impl;
+    };
+    
+    struct abstract_non_coherent_tail_mean
+      : depends_on<>
+    {
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::non_coherent_tail_mean;
+// extract::coherent_tail_mean;
+//
+namespace extract
+{
+    extractor<tag::abstract_non_coherent_tail_mean> const non_coherent_tail_mean = {};
+    extractor<tag::tail_mean> const coherent_tail_mean = {};
+}
+
+using extract::non_coherent_tail_mean;
+using extract::coherent_tail_mean;
+
+// for the purposes of feature-based dependency resolution,
+// coherent_tail_mean<LeftRight> provides the same feature as tail_mean
+template<typename LeftRight>
+struct feature_of<tag::coherent_tail_mean<LeftRight> >
+  : feature_of<tag::tail_mean>
+{
+};
+
+template<typename LeftRight>
+struct feature_of<tag::non_coherent_tail_mean<LeftRight> >
+  : feature_of<tag::abstract_non_coherent_tail_mean>
+{
+};
+
+// So that non_coherent_tail_mean can be automatically substituted 
+// with weighted_non_coherent_tail_mean when the weight parameter is non-void.
+template<typename LeftRight>
+struct as_weighted_feature<tag::non_coherent_tail_mean<LeftRight> >
+{
+    typedef tag::non_coherent_weighted_tail_mean<LeftRight> type;
+};
+
+template<typename LeftRight>
+struct feature_of<tag::non_coherent_weighted_tail_mean<LeftRight> >
+  : feature_of<tag::non_coherent_tail_mean<LeftRight> >
+{};
+
+// NOTE that non_coherent_tail_mean cannot be feature-grouped with tail_mean,
+// which is the base feature for coherent tail means, since (at least for
+// non-continuous distributions) non_coherent_tail_mean is a different measure!
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/tail_quantile.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/tail_quantile.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,146 @@
+///////////////////////////////////////////////////////////////////////////////
+// tail_quantile.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_TAIL_QUANTILE_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_TAIL_QUANTILE_HPP_DE_01_01_2006
+
+#include <vector>
+#include <limits>
+#include <functional>
+#include <sstream>
+#include <stdexcept>
+#include <boost/throw_exception.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/mpl/if.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/tail.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{  
+    ///////////////////////////////////////////////////////////////////////////////
+    // tail_quantile_impl
+    //  Tail quantile estimation based on order statistics
+    /**
+        @brief Tail quantile estimation based on order statistics (for both left and right tails)
+
+        The estimation of a tail quantile \f$\hat{q}\f$ with level \f$\alpha\f$ based on order statistics requires the 
+        chaching of at least the \f$\lceil n\alpha\rceil\f$ smallest or the \f$\lceil n(1-\alpha)\rceil\f$ largest samples, 
+        \f$n\f$ being the total number of samples. The largest of the \f$\lceil n\alpha\rceil\f$ smallest samples or the 
+        smallest of the \f$\lceil n(1-\alpha)\rceil\f$ largest samples provides an estimate for the quantile:
+        
+        \f[
+            \hat{q}_{n,\alpha} = X_{\lceil \alpha n \rceil:n}
+        \f]
+        
+        @param quantile_probability
+    */
+    template<typename Sample, typename LeftRight>
+    struct tail_quantile_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef Sample result_type;
+        
+        tail_quantile_impl(dont_care) {}
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            std::size_t cnt = count(args);
+            
+            std::size_t n = static_cast<std::size_t>(
+                std::ceil(
+                    cnt * ( ( is_same<LeftRight, left>::value ) ? args[quantile_probability] : 1. - args[quantile_probability] )
+                )
+            );
+            
+            // If n is in a valid range, return result, otherwise return NaN or throw exception
+            if ( n < tail(args).size())
+            {
+               // Note that the cached samples of the left are sorted in ascending order, 
+               // whereas the samples of the right tail are sorted in descending order
+               return *(boost::begin(tail(args)) + n - 1);
+            }
+            else
+            {
+                if (std::numeric_limits<result_type>::has_quiet_NaN)
+                {
+                    return std::numeric_limits<result_type>::quiet_NaN();
+                }
+                else
+                {
+                    std::ostringstream msg;
+                    msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")";
+                    boost::throw_exception(std::runtime_error(msg.str()));
+                    return Sample(0);
+                }
+            }
+        }
+    };
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::tail_quantile<>
+//
+namespace tag
+{
+    template<typename LeftRight>
+    struct tail_quantile
+      : depends_on<count, tail<LeftRight> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::tail_quantile_impl<mpl::_1, LeftRight> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::tail_quantile
+//
+namespace extract
+{
+    extractor<tag::quantile> const tail_quantile = {};
+}
+
+using extract::tail_quantile;
+
+// for the purposes of feature-based dependency resolution,
+// tail_quantile<LeftRight> provide the same feature as quantile
+template<typename LeftRight>
+struct feature_of<tag::tail_quantile<LeftRight> >
+  : feature_of<tag::quantile>
+{
+};
+
+// So that tail_quantile can be automatically substituted with
+// weighted_tail_quantile when the weight parameter is non-void.
+template<typename LeftRight>
+struct as_weighted_feature<tag::tail_quantile<LeftRight> >
+{
+    typedef tag::weighted_tail_quantile<LeftRight> type;
+};
+
+template<typename LeftRight>
+struct feature_of<tag::weighted_tail_quantile<LeftRight> >
+  : feature_of<tag::tail_quantile<LeftRight> >
+{};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/tail_variate.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/tail_variate.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,138 @@
+///////////////////////////////////////////////////////////////////////////////
+// tail_variate.hpp
+//
+//  Copyright 2005 Eric Niebler, Michael Gauckler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_STAT_STATISTICS_TAIL_VARIATE_HPP_EAN_28_10_2005
+#define BOOST_STAT_STATISTICS_TAIL_VARIATE_HPP_EAN_28_10_2005
+
+#include <boost/range.hpp>
+#include <boost/mpl/always.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/iterator/reverse_iterator.hpp>
+#include <boost/iterator/permutation_iterator.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/tail.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // tail_variate_impl
+    template<typename VariateType, typename VariateTag, typename LeftRight>
+    struct tail_variate_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef
+            typename detail::tail_range<
+                typename std::vector<VariateType>::const_iterator
+              , std::vector<std::size_t>::iterator
+            >::type
+        result_type;
+
+        template<typename Args>
+        tail_variate_impl(Args const &args)
+          : variates(args[tag::tail<LeftRight>::cache_size], args[parameter::keyword<VariateTag>::get() | VariateType()])
+        {
+        }
+
+        template<typename Args>
+        void assign(Args const &args, std::size_t index)
+        {
+            this->variates[index] = args[parameter::keyword<VariateTag>::get()];
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            // getting the order result causes the indices vector to be sorted.
+            extractor<tag::tail<LeftRight> > const some_tail = {};
+            return this->do_result(some_tail(args));
+        }
+
+    private:
+        template<typename TailRng>
+        result_type do_result(TailRng const &rng) const
+        {
+            return detail::make_tail_range(
+                this->variates.begin()
+              , rng.end().base().base()   // the index iterator
+              , rng.begin().base().base() // (begin and end reversed because these are reverse iterators)
+            );
+        }
+
+        std::vector<VariateType> variates;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::tail_variate<>
+//
+namespace tag
+{
+    template<typename VariateType, typename VariateTag, typename LeftRight>
+    struct tail_variate
+      : depends_on<tail<LeftRight> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef mpl::always<accumulators::impl::tail_variate_impl<VariateType, VariateTag, LeftRight> > impl;
+    };
+    
+    struct abstract_tail_variate
+      : depends_on<>
+    {
+    };
+
+    template<typename LeftRight>
+    struct tail_weights
+      : depends_on<tail<LeftRight> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::tail_variate_impl<mpl::_2, tag::weight, LeftRight> impl;
+    };
+    
+    struct abstract_tail_weights
+      : depends_on<>
+    {
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::tail_variate
+// extract::tail_weights
+//
+namespace extract
+{
+    extractor<tag::abstract_tail_variate> const tail_variate = {};
+    extractor<tag::abstract_tail_weights> const tail_weights = {};
+}
+
+using extract::tail_variate;
+using extract::tail_weights;
+
+template<typename VariateType, typename VariateTag, typename LeftRight>
+struct feature_of<tag::tail_variate<VariateType, VariateTag, LeftRight> >
+  : feature_of<tag::abstract_tail_variate>
+{
+};
+
+template<typename LeftRight>
+struct feature_of<tag::tail_weights<LeftRight> >
+{
+    typedef tag::abstract_tail_weights type;
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/tail_variate_means.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/tail_variate_means.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,249 @@
+///////////////////////////////////////////////////////////////////////////////
+// tail_variate_means.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_TAIL_VARIATE_MEANS_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_TAIL_VARIATE_MEANS_HPP_DE_01_01_2006
+
+#include <numeric>
+#include <vector>
+#include <limits>
+#include <functional>
+#include <sstream>
+#include <stdexcept>
+#include <boost/throw_exception.hpp>
+#include <boost/lambda/lambda.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/tail.hpp>
+#include <boost/accumulators/statistics/tail_variate.hpp>
+#include <boost/accumulators/statistics/tail_mean.hpp>
+#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{       
+    /**
+        @brief Estimation of the absolute and relative tail variate means (for both left and right tails)
+
+        For all \f$j\f$-th variates associated to the \f$\lceil n(1-\alpha)\rceil\f$ largest samples (or the 
+        \f$\lceil n(1-\alpha)\rceil\f$ smallest samples in case of the left tail), the absolute tail means 
+        \f$\widehat{ATM}_{n,\alpha}(X, j)\f$ are computed and returned as an iterator range. Alternatively, 
+        the relative tail means \f$\widehat{RTM}_{n,\alpha}(X, j)\f$ are returned, which are the absolute 
+        tail means normalized with the (non-coherent) sample tail mean \f$\widehat{NCTM}_{n,\alpha}(X)\f$.
+        
+        \f[
+            \widehat{ATM}_{n,\alpha}^{\mathrm{right}}(X, j) = 
+                \frac{1}{\lceil n(1-\alpha) \rceil}
+                \sum_{i=\lceil \alpha n \rceil}^n \xi_{j,i}
+        \f]
+        
+        \f[
+            \widehat{ATM}_{n,\alpha}^{\mathrm{left}}(X, j) = 
+                \frac{1}{\lceil n\alpha \rceil}
+                \sum_{i=1}^{\lceil n\alpha \rceil} \xi_{j,i}
+        \f]
+        
+        \f[
+            \widehat{RTM}_{n,\alpha}^{\mathrm{right}}(X, j) = 
+                \frac{\sum_{i=\lceil n\alpha \rceil}^n \xi_{j,i}}
+            {\lceil n(1-\alpha)\rceil\widehat{NCTM}_{n,\alpha}^{\mathrm{right}}(X)}
+        \f]
+        
+        \f[
+            \widehat{RTM}_{n,\alpha}^{\mathrm{left}}(X, j) = 
+                \frac{\sum_{i=1}^{\lceil n\alpha \rceil} \xi_{j,i}}
+            {\lceil n\alpha\rceil\widehat{NCTM}_{n,\alpha}^{\mathrm{left}}(X)}
+        \f]
+    */
+    
+    ///////////////////////////////////////////////////////////////////////////////
+    // tail_variate_means_impl
+    //  by default: absolute tail_variate_means
+    template<typename Sample, typename Impl, typename LeftRight, typename VariateTag>
+    struct tail_variate_means_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        typedef std::vector<float_type> array_type;
+        // for boost::result_of
+        typedef iterator_range<typename array_type::iterator> result_type;
+        
+        tail_variate_means_impl(dont_care) {}
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            std::size_t cnt = count(args);
+        
+            std::size_t n = static_cast<std::size_t>(
+                std::ceil(
+                    cnt * ( ( is_same<LeftRight, left>::value ) ? args[quantile_probability] : 1. - args[quantile_probability] )
+                )
+            );
+            
+            std::size_t num_variates = tail_variate(args).begin()->size();
+            
+            this->tail_means_.clear();
+            this->tail_means_.resize(num_variates, Sample(0));
+
+            // If n is in a valid range, return result, otherwise return NaN or throw exception
+            if (n < tail(args).size())
+            {     
+                this->tail_means_ = std::accumulate(
+                    tail_variate(args).begin()
+                  , tail_variate(args).begin() + n
+                  , this->tail_means_
+                  , numeric::plus
+                );
+                
+                float_type factor = n * ( (is_same<Impl, relative>::value) ? non_coherent_tail_mean(args) : 1. );
+                
+                using boost::lambda::_1;
+
+                std::transform(
+                    this->tail_means_.begin()
+                  , this->tail_means_.end()
+                  , this->tail_means_.begin()
+                  , _1 / factor
+                );           
+            }  
+            else
+            {
+                if (std::numeric_limits<float_type>::has_quiet_NaN)
+                {
+                    std::fill(
+                        this->tail_means_.begin()
+                      , this->tail_means_.end()
+                      , std::numeric_limits<float_type>::quiet_NaN()
+                    );
+                }
+                else
+                {
+                    std::ostringstream msg;
+                    msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")";
+                    boost::throw_exception(std::runtime_error(msg.str()));
+                }
+            }          
+            return make_iterator_range(this->tail_means_);
+        }
+
+    private:
+    
+        mutable array_type tail_means_;
+    
+    };
+    
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::absolute_tail_variate_means
+// tag::relative_tail_variate_means
+//
+namespace tag
+{
+    template<typename LeftRight, typename VariateType, typename VariateTag>
+    struct absolute_tail_variate_means
+      : depends_on<count, non_coherent_tail_mean<LeftRight>, tail_variate<VariateType, VariateTag, LeftRight> >
+    {
+        typedef accumulators::impl::tail_variate_means_impl<mpl::_1, absolute, LeftRight, VariateTag> impl;
+    };
+    template<typename LeftRight, typename VariateType, typename VariateTag>  
+    struct relative_tail_variate_means
+      : depends_on<count, non_coherent_tail_mean<LeftRight>, tail_variate<VariateType, VariateTag, LeftRight> >
+    {
+        typedef accumulators::impl::tail_variate_means_impl<mpl::_1, relative, LeftRight, VariateTag> impl;
+    };
+    struct abstract_absolute_tail_variate_means
+      : depends_on<>
+    {
+    };
+    struct abstract_relative_tail_variate_means
+      : depends_on<>
+    {
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::tail_variate_means
+// extract::relative_tail_variate_means
+//
+namespace extract
+{
+    extractor<tag::abstract_absolute_tail_variate_means> const tail_variate_means = {};
+    extractor<tag::abstract_relative_tail_variate_means> const relative_tail_variate_means = {};
+}
+
+using extract::tail_variate_means;
+using extract::relative_tail_variate_means;
+
+// tail_variate_means<LeftRight, VariateType, VariateTag>(absolute) -> absolute_tail_variate_means<LeftRight, VariateType, VariateTag>
+template<typename LeftRight, typename VariateType, typename VariateTag>
+struct as_feature<tag::tail_variate_means<LeftRight, VariateType, VariateTag>(absolute)>
+{
+    typedef tag::absolute_tail_variate_means<LeftRight, VariateType, VariateTag> type;
+};
+
+// tail_variate_means<LeftRight, VariateType, VariateTag>(relative) ->relative_tail_variate_means<LeftRight, VariateType, VariateTag>
+template<typename LeftRight, typename VariateType, typename VariateTag>
+struct as_feature<tag::tail_variate_means<LeftRight, VariateType, VariateTag>(relative)>
+{
+    typedef tag::relative_tail_variate_means<LeftRight, VariateType, VariateTag> type;
+};
+
+// Provides non-templatized extractor
+template<typename LeftRight, typename VariateType, typename VariateTag>
+struct feature_of<tag::absolute_tail_variate_means<LeftRight, VariateType, VariateTag> >
+  : feature_of<tag::abstract_absolute_tail_variate_means>
+{
+};
+
+// Provides non-templatized extractor
+template<typename LeftRight, typename VariateType, typename VariateTag>
+struct feature_of<tag::relative_tail_variate_means<LeftRight, VariateType, VariateTag> >
+  : feature_of<tag::abstract_relative_tail_variate_means>
+{
+};
+
+// So that absolute_tail_means can be automatically substituted 
+// with absolute_weighted_tail_means when the weight parameter is non-void.
+template<typename LeftRight, typename VariateType, typename VariateTag>
+struct as_weighted_feature<tag::absolute_tail_variate_means<LeftRight, VariateType, VariateTag> >
+{
+    typedef tag::absolute_weighted_tail_variate_means<LeftRight, VariateType, VariateTag> type;
+};
+
+template<typename LeftRight, typename VariateType, typename VariateTag>
+struct feature_of<tag::absolute_weighted_tail_variate_means<LeftRight, VariateType, VariateTag> >
+  : feature_of<tag::absolute_tail_variate_means<LeftRight, VariateType, VariateTag> >
+{
+};
+
+// So that relative_tail_means can be automatically substituted 
+// with relative_weighted_tail_means when the weight parameter is non-void.
+template<typename LeftRight, typename VariateType, typename VariateTag>
+struct as_weighted_feature<tag::relative_tail_variate_means<LeftRight, VariateType, VariateTag> >
+{
+    typedef tag::relative_weighted_tail_variate_means<LeftRight, VariateType, VariateTag> type;
+};
+
+template<typename LeftRight, typename VariateType, typename VariateTag>
+struct feature_of<tag::relative_weighted_tail_variate_means<LeftRight, VariateType, VariateTag> >
+  : feature_of<tag::relative_tail_variate_means<LeftRight, VariateType, VariateTag> >
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/times2_iterator.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/times2_iterator.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,58 @@
+///////////////////////////////////////////////////////////////////////////////
+// times2_iterator.hpp
+//
+//  Copyright 2006 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_TIMES2_ITERATOR_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_TIMES2_ITERATOR_HPP_DE_01_01_2006
+
+#include <functional>
+#include <boost/range/begin.hpp>
+#include <boost/range/end.hpp>
+#include <boost/range/iterator_range.hpp>
+#include <boost/iterator/transform_iterator.hpp>
+#include <boost/iterator/counting_iterator.hpp>
+#include <boost/iterator/permutation_iterator.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace detail
+{
+    typedef transform_iterator<
+        std::binder1st<std::multiplies<std::size_t> >
+      , counting_iterator<std::size_t>
+    > times2_iterator;
+
+    inline times2_iterator make_times2_iterator(std::size_t i)
+    {
+        return make_transform_iterator(
+            make_counting_iterator(i)
+          , std::bind1st(std::multiplies<std::size_t>(), 2)
+        );
+    }
+
+    
+    ///////////////////////////////////////////////////////////////////////////////
+    // lvalue_index_iterator
+    template<typename Base>
+    struct lvalue_index_iterator
+      : Base
+    {
+        lvalue_index_iterator(Base base)
+          : Base(base)
+        {
+        }
+
+        typename Base::reference operator [](typename Base::difference_type n) const
+        {
+            return *(*this + n);
+        }
+    };
+} // namespace detail
+
+}}
+
+#endif

Added: trunk/boost/accumulators/statistics/variance.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/variance.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,235 @@
+///////////////////////////////////////////////////////////////////////////////
+// variance.hpp
+//
+//  Copyright 2005 Daniel Egloff, Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_VARIANCE_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_VARIANCE_HPP_EAN_28_10_2005
+
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/sum.hpp>
+#include <boost/accumulators/statistics/mean.hpp>
+#include <boost/accumulators/statistics/moment.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    //! Lazy calculaation of variance.
+    /*!
+        Default sample variance implementation based on the second moment \f$ M_n^{(2)} \f$ moment<2>, mean and count.
+        \f[
+            \sigma_n^2 = M_n^{(2)} - \mu_n^2.
+        \f]   
+        where 
+        \f[
+            \mu_n = \frac{1}{n} \sum_{i = 1}^n x_i.
+        \f]   
+        is the estimate of the sample mean and \f$n\f$ is the number of samples. 
+    */
+    template<typename Sample, typename MeanFeature>
+    struct variance_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type result_type;
+
+        variance_impl(dont_care) {}
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            extractor<MeanFeature> mean;
+            result_type tmp = mean(args);
+            return moment<2>(args) - tmp * tmp;
+        }
+    };
+
+    //! Iterative calculation of variance.
+    /*!
+        Iterative calculation of sample variance \f$\sigma_n^2\f$ according to the formula
+        \f[
+            \sigma_n^2 = \frac{1}{n} \sum_{i = 1}^n (x_i - \mu_n)^2 = \frac{n-1}{n} \sigma_{n-1}^2 + \frac{1}{n-1}(x_n - \mu_n)^2.
+        \f]   
+        where 
+        \f[
+            \mu_n = \frac{1}{n} \sum_{i = 1}^n x_i.
+        \f]   
+        is the estimate of the sample mean and \f$n\f$ is the number of samples. 
+        
+        Note that the sample variance is not defined for \f$n <= 1\f$.
+        
+        A simplification can be obtained by the approximate recursion 
+        \f[
+            \sigma_n^2 \approx \frac{n-1}{n} \sigma_{n-1}^2 + \frac{1}{n}(x_n - \mu_n)^2.
+        \f]   
+        because the difference 
+        \f[
+            \left(\frac{1}{n-1} - \frac{1}{n}\right)(x_n - \mu_n)^2 = \frac{1}{n(n-1)}(x_n - \mu_n)^2.
+        \f]   
+        converges to zero as \f$n \rightarrow \infty\f$. However, for small \f$ n \f$ the difference 
+        can be non-negligible.
+    */
+    template<typename Sample, typename MeanFeature, typename Tag>
+    struct immediate_variance_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type result_type;
+
+        template<typename Args>
+        immediate_variance_impl(Args const &args)
+          : variance(numeric::average(args[sample | Sample()], numeric::one<std::size_t>::value))
+        {
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            std::size_t cnt = count(args);
+
+            if(cnt > 1)
+            {
+                extractor<MeanFeature> mean;
+                result_type tmp = args[parameter::keyword<Tag>::get()] - mean(args);
+                this->variance =
+                    numeric::average(this->variance * (cnt - 1), cnt)
+                  + numeric::average(tmp * tmp, cnt - 1);
+            }
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->variance;
+        }
+
+    private:
+        result_type variance;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::variance
+// tag::immediate_variance
+//
+namespace tag
+{
+    struct variance
+      : depends_on<moment<2>, mean>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::variance_impl<mpl::_1, mean> impl;
+    };
+    struct immediate_variance
+      : depends_on<count, immediate_mean>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::immediate_variance_impl<mpl::_1, mean, sample> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::variance
+// extract::immediate_variance
+//
+namespace extract
+{
+    extractor<tag::variance> const variance = {};
+    extractor<tag::immediate_variance> const immediate_variance = {};
+}
+
+using extract::variance;
+using extract::immediate_variance;
+
+// variance(lazy) -> variance
+template<>
+struct as_feature<tag::variance(lazy)>
+{
+    typedef tag::variance type;
+};
+
+// variance(immediate) -> immediate_variance
+template<>
+struct as_feature<tag::variance(immediate)>
+{
+    typedef tag::immediate_variance type;
+};
+
+// for the purposes of feature-based dependency resolution,
+// immediate_variance provides the same feature as variance
+template<>
+struct feature_of<tag::immediate_variance>
+  : feature_of<tag::variance>
+{
+};
+
+// So that variance can be automatically substituted with
+// weighted_variance when the weight parameter is non-void.
+template<>
+struct as_weighted_feature<tag::variance>
+{
+    typedef tag::weighted_variance type;
+};
+
+// for the purposes of feature-based dependency resolution,
+// weighted_variance provides the same feature as variance
+template<>
+struct feature_of<tag::weighted_variance>
+  : feature_of<tag::variance>
+{
+};
+
+// So that immediate_variance can be automatically substituted with
+// immediate_weighted_variance when the weight parameter is non-void.
+template<>
+struct as_weighted_feature<tag::immediate_variance>
+{
+    typedef tag::immediate_weighted_variance type;
+};
+
+// for the purposes of feature-based dependency resolution,
+// immediate_weighted_variance provides the same feature as immediate_variance
+template<>
+struct feature_of<tag::immediate_weighted_variance>
+  : feature_of<tag::immediate_variance>
+{
+};
+
+
+////////////////////////////////////////////////////////////////////////////
+//// droppable_accumulator<variance_impl>
+////  need to specialize droppable lazy variance to cache the result at the
+////  point the accumulator is dropped.
+///// INTERNAL ONLY
+/////
+//template<typename Sample, typename MeanFeature>
+//struct droppable_accumulator<impl::variance_impl<Sample, MeanFeature> >
+//  : droppable_accumulator_base<
+//        with_cached_result<impl::variance_impl<Sample, MeanFeature> >
+//    >
+//{
+//    template<typename Args>
+//    droppable_accumulator(Args const &args)
+//      : droppable_accumulator_base<
+//            with_cached_result<impl::variance_impl<Sample, MeanFeature> >
+//        >(args)
+//    {
+//    }
+//};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/variates/covariate.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/variates/covariate.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,21 @@
+///////////////////////////////////////////////////////////////////////////////
+// weight.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_VARIATES_COVARIATE_HPP_EAN_03_11_2005
+#define BOOST_ACCUMULATORS_STATISTICS_VARIATES_COVARIATE_HPP_EAN_03_11_2005
+
+#include <boost/parameter/keyword.hpp>
+
+namespace boost { namespace accumulators
+{
+
+BOOST_PARAMETER_KEYWORD(tag, covariate1)
+BOOST_PARAMETER_KEYWORD(tag, covariate2)
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_covariance.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_covariance.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,132 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_covariance.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_COVARIANCE_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_COVARIANCE_HPP_DE_01_01_2006
+
+#include <vector>
+#include <limits>
+#include <numeric>
+#include <functional>
+#include <complex>
+#include <boost/mpl/assert.hpp>
+#include <boost/mpl/bool.hpp>
+#include <boost/range.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/lambda/lambda.hpp>
+#include <boost/numeric/ublas/io.hpp>
+#include <boost/numeric/ublas/matrix.hpp>
+#include <boost/type_traits/is_scalar.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/covariance.hpp> // for numeric::outer_product() and type traits
+#include <boost/accumulators/statistics/weighted_mean.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{   
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_covariance_impl
+    //
+    /**
+        @brief Weighted Covariance Estimator
+
+        An iterative Monte Carlo estimator for the weighted covariance \f$\mathrm{Cov}(X,X')\f$, where \f$X\f$ is a sample 
+        and \f$X'\f$ a variate, is given by:
+
+        \f[
+            \hat{c}_n = \frac{\bar{w}_n-w_n}{\bar{w}_n} \hat{c}_{n-1} + \frac{w_n}{\bar{w}_n-w_n}(X_n - \hat{\mu}_n)(X_n' - \hat{\mu}_n'),
+            \quad n\ge2,\quad\hat{c}_1 = 0,
+        \f]
+        
+        \f$\hat{\mu}_n\f$ and \f$\hat{\mu}_n'\f$ being the weighted means of the samples and variates and 
+        \f$\bar{w}_n\f$ the sum of the \f$n\f$ first weights \f$w_i\f$.
+    */
+    template<typename Sample, typename Weight, typename VariateType, typename VariateTag>
+    struct weighted_covariance_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Weight, typename numeric::functional::average<Sample, std::size_t>::result_type>::result_type weighted_sample_type;
+        typedef typename numeric::functional::multiplies<Weight, typename numeric::functional::average<VariateType, std::size_t>::result_type>::result_type weighted_variate_type;
+        // for boost::result_of
+        typedef typename numeric::functional::outer_product<weighted_sample_type, weighted_variate_type>::result_type result_type;
+    
+        template<typename Args>
+        weighted_covariance_impl(Args const &args)
+          : cov_(
+                numeric::outer_product(
+                    numeric::average(args[sample | Sample()], (std::size_t)1)
+                      * numeric::one<Weight>::value
+                  , numeric::average(args[parameter::keyword<VariateTag>::get() | VariateType()], (std::size_t)1)
+                      * numeric::one<Weight>::value
+                )
+            )
+        {
+        }
+        
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            std::size_t cnt = count(args);
+            
+            if (cnt > 1)
+            {
+                extractor<tag::weighted_mean_of_variates<VariateType, VariateTag> > const some_weighted_mean_of_variates = {};
+                
+                this->cov_ = this->cov_ * (sum_of_weights(args) - args[weight]) / sum_of_weights(args)
+                           + numeric::outer_product(
+                                 some_weighted_mean_of_variates(args) - args[parameter::keyword<VariateTag>::get()]
+                               , weighted_mean(args) - args[sample]
+                             ) * args[weight] / (sum_of_weights(args) - args[weight]);
+            }
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->cov_;
+        }
+
+    private:
+        result_type cov_;
+    };
+    
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_covariance
+//
+namespace tag
+{
+    template<typename VariateType, typename VariateTag>
+    struct weighted_covariance
+      : depends_on<count, sum_of_weights, weighted_mean, weighted_mean_of_variates<VariateType, VariateTag> >
+    {
+        typedef accumulators::impl::weighted_covariance_impl<mpl::_1, mpl::_2, VariateType, VariateTag> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_covariance
+//
+namespace extract
+{
+    extractor<tag::abstract_covariance> const weighted_covariance = {};
+}
+
+using extract::weighted_covariance;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_density.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_density.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,219 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_density.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_DENSITY_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_DENSITY_HPP_DE_01_01_2006
+
+#include <vector>
+#include <limits>
+#include <functional>
+#include <boost/range.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/sum.hpp>
+#include <boost/accumulators/statistics/max.hpp>
+#include <boost/accumulators/statistics/min.hpp>
+#include <boost/accumulators/statistics/density.hpp> // for named parameters density_cache_size and density_num_bins
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{       
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_density_impl
+    //  density histogram for weighted samples
+    /**
+        @brief Histogram density estimator for weighted samples
+
+        The histogram density estimator returns a histogram of the sample distribution. The positions and sizes of the bins 
+        are determined using a specifiable number of cached samples (cache_size). The range between the minimum and the 
+        maximum of the cached samples is subdivided into a specifiable number of bins (num_bins) of same size. Additionally, 
+        an under- and an overflow bin is added to capture future under- and overflow samples. Once the bins are determined, 
+        the cached samples and all subsequent samples are added to the correct bins. At the end, a range of std::pair is 
+        returned, where each pair contains the position of the bin (lower bound) and the sum of the weights (normalized with the 
+        sum of all weights).
+
+        @param density_cache_size Number of first samples used to determine min and max.
+        @param density_num_bins Number of bins (two additional bins collect under- and overflow samples). 
+    */
+    template<typename Sample, typename Weight>
+    struct weighted_density_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Weight, std::size_t>::result_type float_type;
+        typedef std::vector<std::pair<float_type, float_type> > histogram_type;
+        typedef std::vector<float_type> array_type;
+        // for boost::result_of
+        typedef iterator_range<typename histogram_type::iterator> result_type;
+        
+        template<typename Args>
+        weighted_density_impl(Args const &args)
+            : cache_size(args[density_cache_size])
+            , cache(cache_size)
+            , num_bins(args[density_num_bins])
+            , samples_in_bin(num_bins + 2, 0.)
+            , bin_positions(num_bins + 2)
+            , histogram(
+                num_bins + 2
+              , std::make_pair(
+                    numeric::average(args[sample | Sample()],(std::size_t)1)
+                  , numeric::average(args[sample | Sample()],(std::size_t)1)
+                )
+              )
+            , is_dirty(true)
+        {
+        }
+        
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            this->is_dirty = true;
+        
+            std::size_t cnt = count(args);
+            
+            // Fill up cache with cache_size first samples
+            if (cnt <= this->cache_size)
+            {
+                this->cache[cnt - 1] = std::make_pair(args[sample], args[weight]);
+            }
+            
+            // Once cache_size samples have been accumulated, create num_bins bins of same size between 
+            // the minimum and maximum of the cached samples as well as an under- and an overflow bin. 
+            // Store their lower bounds (bin_positions) and fill the bins with the cached samples (samples_in_bin).
+            if (cnt == this->cache_size)
+            {
+                float_type minimum = numeric::average((min)(args),(std::size_t)1);
+                float_type maximum = numeric::average((max)(args),(std::size_t)1);
+                float_type bin_size = numeric::average(maximum - minimum, this->num_bins);
+                
+                // determine bin positions (their lower bounds)
+                for (std::size_t i = 0; i < this->num_bins + 2; ++i) 
+                {
+                    this->bin_positions[i] = minimum + (i - 1.) * bin_size;
+                }
+                
+                for (typename histogram_type::const_iterator iter = this->cache.begin(); iter != this->cache.end(); ++iter)
+                {
+                    if (iter->first < this->bin_positions[1])
+                    {
+                        this->samples_in_bin[0] += iter->second;
+                    }
+                    else if (iter->first >= this->bin_positions[this->num_bins + 1])
+                    {
+                        this->samples_in_bin[this->num_bins + 1] += iter->second;
+                    }    
+                    else
+                    {
+                        typename array_type::iterator it = std::upper_bound(
+                            this->bin_positions.begin()
+                          , this->bin_positions.end()
+                          , iter->first
+                        );
+                        
+                        std::size_t d = std::distance(this->bin_positions.begin(), it);
+                        this->samples_in_bin[d - 1] += iter->second;
+                    }
+                }
+            }
+            // Add each subsequent sample to the correct bin
+            else if (cnt > this->cache_size)
+            {
+                if (args[sample] < this->bin_positions[1])
+                {
+                    this->samples_in_bin[0] += args[weight];
+                }
+                else if (args[sample] >= this->bin_positions[this->num_bins + 1])
+                {
+                    this->samples_in_bin[this->num_bins + 1] += args[weight];
+                }
+                else
+                {
+                    typename array_type::iterator it = std::upper_bound(
+                        this->bin_positions.begin()
+                      , this->bin_positions.end()
+                      , args[sample]
+                    );
+                    
+                    std::size_t d = std::distance(this->bin_positions.begin(), it);
+                    this->samples_in_bin[d - 1] += args[weight];
+                }
+            }        
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            if (this->is_dirty)
+            {
+                this->is_dirty = false;
+                
+                // creates a vector of std::pair where each pair i holds
+                // the values bin_positions[i] (x-axis of histogram) and
+                // samples_in_bin[i] / cnt (y-axis of histogram).
+    
+                for (std::size_t i = 0; i < this->num_bins + 2; ++i)
+                {
+                    this->histogram[i] = std::make_pair(this->bin_positions[i], numeric::average(this->samples_in_bin[i], sum_of_weights(args)));
+                }
+            }
+                
+            // returns a range of pairs            
+            return make_iterator_range(this->histogram);
+        }
+
+    private:
+        std::size_t            cache_size;      // number of cached samples
+        histogram_type         cache;           // cache to store the first cache_size samples with their weights as std::pair
+        std::size_t            num_bins;        // number of bins
+        array_type             samples_in_bin;  // number of samples in each bin
+        array_type             bin_positions;   // lower bounds of bins
+        mutable histogram_type histogram;       // histogram
+        mutable bool is_dirty;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_density
+//
+namespace tag
+{
+    struct weighted_density
+      : depends_on<count, sum_of_weights, min, max>
+      , density_cache_size
+      , density_num_bins
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::weighted_density_impl<mpl::_1, mpl::_2> impl;
+        
+        #ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED
+        static boost::parameter::keyword<density_cache_size> const cache_size;
+        static boost::parameter::keyword<density_num_bins> const num_bins;
+        #endif
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_density
+//
+namespace extract
+{
+    extractor<tag::density> const weighted_density = {};
+}
+
+using extract::weighted_density;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_extended_p_square.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_extended_p_square.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,289 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_extended_p_square.hpp
+//
+//  Copyright 2005 Daniel Egloff. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_EXTENDED_P_SQUARE_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_EXTENDED_P_SQUARE_HPP_DE_01_01_2006
+
+#include <vector>
+#include <functional>
+#include <boost/range/begin.hpp>
+#include <boost/range/end.hpp>
+#include <boost/range/iterator_range.hpp>
+#include <boost/iterator/transform_iterator.hpp>
+#include <boost/iterator/counting_iterator.hpp>
+#include <boost/iterator/permutation_iterator.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/sum.hpp>
+#include <boost/accumulators/statistics/times2_iterator.hpp>
+#include <boost/accumulators/statistics/extended_p_square.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_extended_p_square_impl
+    //  multiple quantile estimation with weighted samples
+    /**
+        @brief Multiple quantile estimation with the extended \f$P^2\f$ algorithm for weighted samples
+
+        This version of the extended \f$P^2\f$ algorithm extends the extended \f$P^2\f$ algorithm to 
+        support weighted samples. The extended \f$P^2\f$ algorithm dynamically estimates several 
+        quantiles without storing samples. Assume that \f$m\f$ quantiles 
+        \f$\xi_{p_1}, \ldots, \xi_{p_m}\f$ are to be estimated. Instead of storing the whole sample 
+        cumulative distribution, the algorithm maintains only \f$m+2\f$ principal markers and 
+        \f$m+1\f$ middle markers, whose positions are updated with each sample and whose heights 
+        are adjusted (if necessary) using a piecewise-parablic formula. The heights of the principal 
+        markers are the current estimates of the quantiles and are returned as an iterator range.
+
+        For further details, see
+        
+        K. E. E. Raatikainen, Simultaneous estimation of several quantiles, Simulation, Volume 49,
+        Number 4 (October), 1986, p. 159-164.
+
+        The extended \f$ P^2 \f$ algorithm generalizess the \f$ P^2 \f$ algorithm of
+
+        R. Jain and I. Chlamtac, The P^2 algorithmus for dynamic calculation of quantiles and
+        histograms without storing observations, Communications of the ACM,
+        Volume 28 (October), Number 10, 1985, p. 1076-1085.
+
+        @param extended_p_square_probabilities A vector of quantile probabilities.
+    */
+    template<typename Sample, typename Weight>
+    struct weighted_extended_p_square_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        typedef typename numeric::functional::average<weighted_sample, std::size_t>::result_type float_type;
+        typedef std::vector<float_type> array_type;
+        // for boost::result_of
+        typedef iterator_range<
+            detail::lvalue_index_iterator<
+                permutation_iterator<
+                    typename array_type::const_iterator
+                  , detail::times2_iterator
+                >
+            >
+        > result_type;
+        
+        template<typename Args>
+        weighted_extended_p_square_impl(Args const &args)
+          : probabilities(
+                boost::begin(args[extended_p_square_probabilities])
+              , boost::end(args[extended_p_square_probabilities])
+            )
+          , heights(2 * probabilities.size() + 3)
+          , actual_positions(heights.size())
+          , desired_positions(heights.size())
+        {
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            std::size_t cnt = count(args);
+            std::size_t sample_cell = 1; // k
+            std::size_t num_quantiles = this->probabilities.size();
+            
+            // m+2 principal markers and m+1 middle markers
+            std::size_t num_markers = 2 * num_quantiles + 3;
+                        
+            // first accumulate num_markers samples
+            if(cnt <= num_markers)
+            {
+                this->heights[cnt - 1] = args[sample];
+                this->actual_positions[cnt - 1] = args[weight];
+                                
+                // complete the initialization of heights (and actual_positions) by sorting
+                if(cnt == num_markers)
+                {
+                    // TODO: we need to sort the initial samples (in heights) in ascending order and 
+                    // sort their weights (in actual_positions) the same way. The following lines do 
+                    // it, but there must be a better and more efficient way of doing this.
+                    typename array_type::iterator it_begin, it_end, it_min;
+                    
+                    it_begin = this->heights.begin();
+                    it_end   = this->heights.end();
+                    
+                    std::size_t pos = 0;
+                    
+                    while (it_begin != it_end)
+                    {
+                        it_min = std::min_element(it_begin, it_end);
+                        std::size_t d = std::distance(it_begin, it_min);
+                        std::swap(*it_begin, *it_min);
+                        std::swap(this->actual_positions[pos], this->actual_positions[pos + d]);
+                        ++it_begin;
+                        ++pos;
+                    }
+                    
+                    // calculate correct initial actual positions
+                    for (std::size_t i = 1; i < num_markers; ++i)
+                    {
+                        actual_positions[i] += actual_positions[i - 1];
+                    }
+                }
+            }
+            else
+            {
+                if(args[sample] < this->heights[0])
+                {
+                    this->heights[0] = args[sample];
+                    this->actual_positions[0] = args[weight];
+                    sample_cell = 1;
+                }
+                else if(args[sample] >= this->heights[num_markers - 1])
+                {
+                    this->heights[num_markers - 1] = args[sample];
+                    sample_cell = num_markers - 1;
+                }
+                else
+                {
+                    // find cell k = sample_cell such that heights[k-1] <= sample < heights[k]
+
+                    typedef typename array_type::iterator iterator;
+                    iterator it = std::upper_bound(
+                        this->heights.begin()
+                      , this->heights.end()
+                      , args[sample]
+                    );
+                    
+                    sample_cell = std::distance(this->heights.begin(), it);
+                }
+
+                // update actual position of all markers above sample_cell
+                for(std::size_t i = sample_cell; i < num_markers; ++i)
+                {
+                    this->actual_positions[i] += args[weight];
+                }
+
+                // compute desired positions
+                {
+                    this->desired_positions[0] = this->actual_positions[0];
+                    this->desired_positions[num_markers - 1] = sum_of_weights(args);
+                    this->desired_positions[1] = (sum_of_weights(args) - this->actual_positions[0]) * probabilities[0]
+                                              / 2. + this->actual_positions[0];
+                    this->desired_positions[num_markers - 2] = (sum_of_weights(args) - this->actual_positions[0]) 
+                                                            * (probabilities[num_quantiles - 1] + 1.) 
+                                                            / 2. + this->actual_positions[0];
+                    
+                    for (std::size_t i = 0; i < num_quantiles; ++i)
+                    {
+                        this->desired_positions[2 * i + 2] = (sum_of_weights(args) - this->actual_positions[0])
+                                                          * probabilities[i] + this->actual_positions[0];
+                    }
+                    
+                    for (std::size_t i = 1; i < num_quantiles; ++i)
+                    {
+                        this->desired_positions[2 * i + 1] = (sum_of_weights(args) - this->actual_positions[0])
+                                                      * (probabilities[i - 1] + probabilities[i]) 
+                                                      / 2. + this->actual_positions[0];
+                    }
+                }
+                                
+                // adjust heights and actual_positions of markers 1 to num_markers - 2 if necessary
+                for (std::size_t i = 1; i <= num_markers - 2; ++i)
+                {
+                    // offset to desired position
+                    float_type d = this->desired_positions[i] - this->actual_positions[i];
+
+                    // offset to next position
+                    float_type dp = this->actual_positions[i + 1] - this->actual_positions[i];
+
+                    // offset to previous position
+                    float_type dm = this->actual_positions[i - 1] - this->actual_positions[i];
+
+                    // height ds
+                    float_type hp = (this->heights[i + 1] - this->heights[i]) / dp;
+                    float_type hm = (this->heights[i - 1] - this->heights[i]) / dm;
+
+                    if((d >= 1 && dp > 1) || (d <= -1 && dm < -1))
+                    {
+                        short sign_d = static_cast<short>(d / std::abs(d));
+
+                        float_type h = this->heights[i] + sign_d / (dp - dm) * ((sign_d - dm)*hp + (dp - sign_d) * hm);
+
+                        // try adjusting heights[i] using p-squared formula
+                        if(this->heights[i - 1] < h && h < this->heights[i + 1])
+                        {
+                            this->heights[i] = h;
+                        }
+                        else
+                        {
+                            // use linear formula
+                            if(d > 0)
+                            {
+                                this->heights[i] += hp;
+                            }
+                            if(d < 0)
+                            {
+                                this->heights[i] -= hm;
+                            }
+                        }
+                        this->actual_positions[i] += sign_d;
+                    }
+                }
+            }
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            // for i in [1,probabilities.size()], return heights[i * 2]
+            detail::times2_iterator idx_begin = detail::make_times2_iterator(1);
+            detail::times2_iterator idx_end = detail::make_times2_iterator(this->probabilities.size() + 1);
+
+            return result_type(
+                make_permutation_iterator(this->heights.begin(), idx_begin)
+              , make_permutation_iterator(this->heights.begin(), idx_end)
+            );
+        }
+        
+    private:
+        array_type probabilities;         // the quantile probabilities
+        array_type heights;               // q_i
+        array_type actual_positions;      // n_i
+        array_type desired_positions;     // d_i
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_extended_p_square
+//
+namespace tag
+{
+    struct weighted_extended_p_square
+      : depends_on<count, sum_of_weights>
+      , extended_p_square_probabilities
+    {
+        typedef accumulators::impl::weighted_extended_p_square_impl<mpl::_1, mpl::_2> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_extended_p_square
+//
+namespace extract
+{
+    extractor<tag::weighted_extended_p_square> const weighted_extended_p_square = {};
+}
+
+using extract::weighted_extended_p_square;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_kurtosis.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_kurtosis.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,103 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_kurtosis.hpp
+//
+//  Copyright 2006 Olivier Gygi, Daniel Egloff. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_KURTOSIS_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_KURTOSIS_HPP_EAN_28_10_2005
+
+#include <limits>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/weighted_moment.hpp>
+#include <boost/accumulators/statistics/weighted_mean.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_kurtosis_impl
+    /**
+        @brief Kurtosis estimation for weighted samples
+
+        The kurtosis of a sample distribution is defined as the ratio of the 4th central moment and the square of the 2nd central 
+        moment (the variance) of the samples, minus 3. The term \f$ -3 \f$ is added in order to ensure that the normal distribution 
+        has zero kurtosis. The kurtosis can also be expressed by the simple moments:
+        
+        \f[
+            \hat{g}_2 = 
+                \frac
+                {\widehat{m}_n^{(4)}-4\widehat{m}_n^{(3)}\hat{\mu}_n+6\widehat{m}_n^{(2)}\hat{\mu}_n^2-3\hat{\mu}_n^4}
+                {\left(\widehat{m}_n^{(2)} - \hat{\mu}_n^{2}\right)^2} - 3,
+        \f]
+        
+        where \f$ \widehat{m}_n^{(i)} \f$ are the \f$ i \f$-th moment and \f$ \hat{\mu}_n \f$ the mean (first moment) of the 
+        \f$ n \f$ samples.
+        
+        The kurtosis estimator for weighted samples is formally identical to the estimator for unweighted samples, except that 
+        the weighted counterparts of all measures it depends on are to be taken.
+    */
+    template<typename Sample, typename Weight>
+    struct weighted_kurtosis_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        // for boost::result_of
+        typedef typename numeric::functional::average<weighted_sample, weighted_sample>::result_type result_type;
+
+        weighted_kurtosis_impl(dont_care)
+        {
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return numeric::average( 
+                        weighted_moment<4>(args) 
+                        - 4. * weighted_moment<3>(args) * weighted_mean(args)
+                        + 6. * weighted_moment<2>(args) * weighted_mean(args) * weighted_mean(args) 
+                        - 3. * weighted_mean(args) * weighted_mean(args) * weighted_mean(args) * weighted_mean(args)
+                      , ( weighted_moment<2>(args) - weighted_mean(args) * weighted_mean(args) ) 
+                        * ( weighted_moment<2>(args) - weighted_mean(args) * weighted_mean(args) )
+                   ) - 3.;
+        }
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_kurtosis
+//
+namespace tag
+{
+    struct weighted_kurtosis
+      : depends_on<weighted_mean, weighted_moment<2>, weighted_moment<3>, weighted_moment<4> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::weighted_kurtosis_impl<mpl::_1, mpl::_2> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_kurtosis
+//
+namespace extract
+{
+    extractor<tag::weighted_kurtosis> const weighted_kurtosis = {};
+}
+
+using extract::weighted_kurtosis;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_mean.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_mean.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,187 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_mean.hpp
+//
+//  Copyright 2006 Eric Niebler, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_MEAN_HPP_EAN_03_11_2005
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_MEAN_HPP_EAN_03_11_2005
+
+#include <boost/mpl/assert.hpp>
+#include <boost/mpl/eval_if.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/weights.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/sum.hpp>
+#include <boost/accumulators/statistics/mean.hpp>
+#include <boost/accumulators/statistics/weighted_sum.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_mean_impl
+    //      lazy, by default
+    template<typename Sample, typename Weight, typename Tag>
+    struct weighted_mean_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        // for boost::result_of
+        typedef typename numeric::functional::average<weighted_sample, Weight>::result_type result_type;
+
+        weighted_mean_impl(dont_care) {}
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            typedef
+                typename mpl::if_<
+                    is_same<Tag, tag::sample>
+                  , tag::weighted_sum
+                  , tag::weighted_sum_of_variates<Sample, Tag>
+                >::type
+            weighted_sum_tag;
+            
+            extractor<weighted_sum_tag> const some_weighted_sum = {};
+            
+            return numeric::average(some_weighted_sum(args), sum_of_weights(args));
+        }
+    };
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // immediate_weighted_mean_impl
+    //      immediate
+    template<typename Sample, typename Weight, typename Tag>
+    struct immediate_weighted_mean_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        // for boost::result_of
+        typedef typename numeric::functional::average<weighted_sample, Weight>::result_type result_type;
+
+        template<typename Args>
+        immediate_weighted_mean_impl(Args const &args)
+          : mean(
+                numeric::average(
+                    args[parameter::keyword<Tag>::get() | Sample()]
+                      * numeric::one<Weight>::value
+                  , numeric::one<Weight>::value
+                )
+            )
+        {
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            // Matthias:
+            //  need to pass the argument pack since the weight might be an external
+            //  accumulator set passed as a named parameter
+            Weight w_sum = sum_of_weights(args);
+            Weight w = args[weight];
+            weighted_sample const &s = args[parameter::keyword<Tag>::get()] * w;
+            this->mean = numeric::average(this->mean * (w_sum - w) + s, w_sum);
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->mean;
+        }
+
+    private:
+        result_type mean;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_mean
+// tag::immediate_weighted_mean
+//
+namespace tag
+{
+    struct weighted_mean
+      : depends_on<sum_of_weights, weighted_sum>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::weighted_mean_impl<mpl::_1, mpl::_2, tag::sample> impl;
+    };
+    struct immediate_weighted_mean
+      : depends_on<sum_of_weights>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::immediate_weighted_mean_impl<mpl::_1, mpl::_2, tag::sample> impl;
+    };
+    template<typename VariateType, typename VariateTag>
+    struct weighted_mean_of_variates
+      : depends_on<sum_of_weights, weighted_sum_of_variates<VariateType, VariateTag> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::weighted_mean_impl<VariateType, mpl::_2, VariateTag> impl;
+    };
+    template<typename VariateType, typename VariateTag>
+    struct immediate_weighted_mean_of_variates
+      : depends_on<sum_of_weights>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::immediate_weighted_mean_impl<VariateType, mpl::_2, VariateTag> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_mean
+// extract::weighted_mean_of_variates
+//
+namespace extract
+{
+    extractor<tag::mean> const weighted_mean = {};
+    BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, weighted_mean_of_variates, (typename)(typename));
+}
+
+using extract::weighted_mean;
+using extract::weighted_mean_of_variates;
+
+// weighted_mean(lazy) -> weighted_mean
+template<>
+struct as_feature<tag::weighted_mean(lazy)>
+{
+    typedef tag::weighted_mean type;
+};
+
+// weighted_mean(immediate) -> immediate_weighted_mean
+template<>
+struct as_feature<tag::weighted_mean(immediate)>
+{
+    typedef tag::immediate_weighted_mean type;
+};
+
+// weighted_mean_of_variates<VariateType, VariateTag>(lazy) -> weighted_mean_of_variates<VariateType, VariateTag>
+template<typename VariateType, typename VariateTag>
+struct as_feature<tag::weighted_mean_of_variates<VariateType, VariateTag>(lazy)>
+{
+    typedef tag::weighted_mean_of_variates<VariateType, VariateTag> type;
+};
+
+// weighted_mean_of_variates<VariateType, VariateTag>(immediate) -> immediate_weighted_mean_of_variates<VariateType, VariateTag>
+template<typename VariateType, typename VariateTag>
+struct as_feature<tag::weighted_mean_of_variates<VariateType, VariateTag>(immediate)>
+{
+    typedef tag::immediate_weighted_mean_of_variates<VariateType, VariateTag> type;
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_median.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_median.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,236 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_median.hpp
+//
+//  Copyright 2006 Eric Niebler, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_MEDIAN_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_MEDIAN_HPP_EAN_28_10_2005
+
+#include <boost/mpl/placeholders.hpp>
+#include <boost/range/iterator_range.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/median.hpp>
+#include <boost/accumulators/statistics/weighted_p_square_quantile.hpp>
+#include <boost/accumulators/statistics/weighted_density.hpp>
+#include <boost/accumulators/statistics/weighted_p_square_cumulative_distribution.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_median_impl
+    //
+    /**
+        @brief Median estimation for weighted samples based on the \f$P^2\f$ quantile estimator
+        
+        The \f$P^2\f$ algorithm for weighted samples is invoked with a quantile probability of 0.5.
+    */
+    template<typename Sample>
+    struct weighted_median_impl
+      : accumulator_base
+    {
+        // for boost::result_of
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type result_type;
+        
+        weighted_median_impl(dont_care) {}
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return weighted_p_square_quantile_for_median(args);
+        }
+    };
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // with_density_weighted_median_impl
+    //
+    /**
+        @brief Median estimation for weighted samples based on the density estimator
+        
+        The algorithm determines the bin in which the \f$0.5*cnt\f$-th sample lies, \f$cnt\f$ being 
+        the total number of samples. It returns the approximate horizontal position of this sample, 
+        based on a linear interpolation inside the bin.
+    */
+    template<typename Sample>
+    struct with_density_weighted_median_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Sample, std::size_t>::result_type float_type;
+        typedef std::vector<std::pair<float_type, float_type> > histogram_type;
+        typedef iterator_range<typename histogram_type::iterator> range_type;
+        // for boost::result_of
+        typedef float_type result_type;
+         
+        template<typename Args>
+        with_density_weighted_median_impl(Args const &args)
+          : sum(numeric::average(args[sample | Sample()], (std::size_t)1))
+          , is_dirty(true)
+        {
+        }
+
+        void operator ()(dont_care)
+        {
+            this->is_dirty = true;
+        }
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            if (this->is_dirty)
+            {
+                this->is_dirty = false;
+            
+                std::size_t cnt = count(args);
+                range_type histogram = weighted_density(args);
+                typename range_type::iterator it = histogram.begin();
+                while (this->sum < 0.5 * cnt)
+                {
+                    this->sum += it->second * cnt;
+                    ++it;
+                }
+                --it;
+                float_type over = numeric::average(this->sum - 0.5 * cnt, it->second * cnt);
+                this->median = it->first * over + (it + 1)->first * ( 1. - over );
+            }
+            
+            return this->median;
+        }
+
+    private:
+        mutable float_type sum;
+        mutable bool is_dirty;
+        mutable float_type median;
+    };
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // with_p_square_cumulative_distribution_weighted_median_impl
+    //
+    /**
+        @brief Median estimation for weighted samples based on the \f$P^2\f$ cumulative distribution estimator
+        
+        The algorithm determines the first (leftmost) bin with a height exceeding 0.5. It 
+        returns the approximate horizontal position of where the cumulative distribution 
+        equals 0.5, based on a linear interpolation inside the bin.
+    */
+    template<typename Sample, typename Weight>
+    struct with_p_square_cumulative_distribution_weighted_median_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        typedef typename numeric::functional::average<weighted_sample, std::size_t>::result_type float_type;
+        typedef std::vector<std::pair<float_type, float_type> > histogram_type;
+        typedef iterator_range<typename histogram_type::iterator> range_type;
+        // for boost::result_of
+        typedef float_type result_type;
+                
+        template<typename Args>
+        with_p_square_cumulative_distribution_weighted_median_impl(Args const &args)
+          : is_dirty(true)
+        {
+        }
+        
+        void operator ()(dont_care)
+        {
+            this->is_dirty = true;
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            if (this->is_dirty)
+            {
+                this->is_dirty = false;
+            
+                range_type histogram = weighted_p_square_cumulative_distribution(args);
+                typename range_type::iterator it = histogram.begin();
+                while (it->second < 0.5)
+                {
+                    ++it;
+                }
+                float_type over = numeric::average(it->second - 0.5, it->second - (it - 1)->second);
+                this->median = it->first * over + (it + 1)->first * ( 1. - over );
+            }
+            
+            return this->median;
+        }
+    private:
+        mutable bool is_dirty;
+        mutable float_type median;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_median
+// tag::with_density_weighted_median
+// tag::with_p_square_cumulative_distribution_weighted_median
+//
+namespace tag
+{
+    struct weighted_median
+      : depends_on<weighted_p_square_quantile_for_median>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::weighted_median_impl<mpl::_1> impl;
+    };
+    struct with_density_weighted_median
+      : depends_on<count, weighted_density>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::with_density_weighted_median_impl<mpl::_1> impl;
+    };
+    struct with_p_square_cumulative_distribution_weighted_median
+      : depends_on<weighted_p_square_cumulative_distribution>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::with_p_square_cumulative_distribution_weighted_median_impl<mpl::_1, mpl::_2> impl;
+    };
+
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_median
+//
+namespace extract
+{
+    extractor<tag::median> const weighted_median = {};
+}
+
+using extract::weighted_median;
+// weighted_median(with_p_square_quantile) -> weighted_median
+template<>
+struct as_feature<tag::weighted_median(with_p_square_quantile)>
+{
+    typedef tag::weighted_median type;
+};
+
+// weighted_median(with_density) -> with_density_weighted_median
+template<>
+struct as_feature<tag::weighted_median(with_density)>
+{
+    typedef tag::with_density_weighted_median type;
+};
+
+// weighted_median(with_p_square_cumulative_distribution) -> with_p_square_cumulative_distribution_weighted_median
+template<>
+struct as_feature<tag::weighted_median(with_p_square_cumulative_distribution)>
+{
+    typedef tag::with_p_square_cumulative_distribution_weighted_median type;
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_moment.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_moment.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,96 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_moment.hpp
+//
+//  Copyright 2006, Eric Niebler, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_MOMENT_HPP_EAN_15_11_2005
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_MOMENT_HPP_EAN_15_11_2005
+
+#include <cmath>
+#include <boost/mpl/int.hpp>
+#include <boost/mpl/assert.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/preprocessor/arithmetic/inc.hpp>
+#include <boost/preprocessor/repetition/repeat_from_to.hpp>
+#include <boost/preprocessor/repetition/enum_trailing_params.hpp>
+#include <boost/preprocessor/repetition/enum_trailing_binary_params.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/moment.hpp> // for pow()
+#include <boost/accumulators/statistics/sum.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_moment_impl
+    template<typename N, typename Sample, typename Weight>
+    struct weighted_moment_impl
+      : accumulator_base // TODO: also depends_on sum of powers
+    {
+        BOOST_MPL_ASSERT_RELATION(N::value, >, 0);
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        // for boost::result_of
+        typedef typename numeric::functional::average<weighted_sample, Weight>::result_type result_type;
+
+        template<typename Args>
+        weighted_moment_impl(Args const &args)
+          : sum(args[sample | Sample()] * numeric::one<Weight>::value)
+        {
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            this->sum += args[weight] * numeric::pow(args[sample], N());
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return numeric::average(this->sum, sum_of_weights(args));
+        }
+
+    private:
+        weighted_sample sum;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_moment
+//
+namespace tag
+{
+    template<int N>
+    struct weighted_moment
+      : depends_on<count, sum_of_weights>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::weighted_moment_impl<mpl::int_<N>, mpl::_1, mpl::_2> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_moment
+//
+namespace extract
+{
+    BOOST_ACCUMULATORS_DEFINE_EXTRACTOR(tag, weighted_moment, (int))
+}
+
+using extract::weighted_moment;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_p_square_cumulative_distribution.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_p_square_cumulative_distribution.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,260 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_p_square_cumulative_distribution.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_P_SQUARE_CUMULATIVE_DISTRIBUTION_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_P_SQUARE_CUMULATIVE_DISTRIBUTION_HPP_DE_01_01_2006
+
+#include <vector>
+#include <functional>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/range.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/sum.hpp>
+#include <boost/accumulators/statistics/p_square_cumulative_distribution.hpp> // for named parameter p_square_cumulative_distribution_num_cells
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_p_square_cumulative_distribution_impl
+    //  cumulative distribution calculation (as histogram)
+    /**
+        @brief Histogram calculation of the cumulative distribution with the \f$P^2\f$ algorithm for weighted samples
+
+        A histogram of the sample cumulative distribution is computed dynamically without storing samples 
+        based on the \f$ P^2 \f$ algorithm for weighted samples. The returned histogram has a specifiable 
+        amount (num_cells) equiprobable (and not equal-sized) cells.
+        
+        Note that applying importance sampling results in regions to be more and other regions to be less 
+        accurately estimated than without importance sampling, i.e., with unweighted samples.
+
+        For further details, see
+
+        R. Jain and I. Chlamtac, The P^2 algorithmus for dynamic calculation of quantiles and 
+        histograms without storing observations, Communications of the ACM,   
+        Volume 28 (October), Number 10, 1985, p. 1076-1085.
+
+        @param p_square_cumulative_distribution_num_cells
+    */
+    template<typename Sample, typename Weight>
+    struct weighted_p_square_cumulative_distribution_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        typedef typename numeric::functional::average<weighted_sample, std::size_t>::result_type float_type;
+        typedef std::vector<std::pair<float_type, float_type> > histogram_type;
+        typedef std::vector<float_type> array_type;
+        // for boost::result_of
+        typedef iterator_range<typename histogram_type::iterator> result_type;
+        
+        template<typename Args>
+        weighted_p_square_cumulative_distribution_impl(Args const &args)
+          : num_cells(args[p_square_cumulative_distribution_num_cells])
+          , heights(num_cells + 1)
+          , actual_positions(num_cells + 1)
+          , desired_positions(num_cells + 1)
+          , histogram(num_cells + 1)
+          , is_dirty(true)
+        {     
+        }
+        
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            this->is_dirty = true;
+        
+            std::size_t cnt = count(args);
+            std::size_t sample_cell = 1; // k
+            std::size_t b = this->num_cells;
+
+            // accumulate num_cells + 1 first samples
+            if (cnt <= b + 1)
+            {
+                this->heights[cnt - 1] = args[sample];
+                this->actual_positions[cnt - 1] = args[weight];
+                
+                // complete the initialization of heights by sorting
+                if (cnt == b + 1)
+                {
+                    //std::sort(this->heights.begin(), this->heights.end());
+                    
+                    // TODO: we need to sort the initial samples (in heights) in ascending order and 
+                    // sort their weights (in actual_positions) the same way. The following lines do 
+                    // it, but there must be a better and more efficient way of doing this.
+                    typename array_type::iterator it_begin, it_end, it_min;
+                    
+                    it_begin = this->heights.begin();
+                    it_end   = this->heights.end();
+                    
+                    std::size_t pos = 0;
+                    
+                    while (it_begin != it_end)
+                    {
+                        it_min = std::min_element(it_begin, it_end);
+                        std::size_t d = std::distance(it_begin, it_min);
+                        std::swap(*it_begin, *it_min);
+                        std::swap(this->actual_positions[pos], this->actual_positions[pos + d]);
+                        ++it_begin;
+                        ++pos;
+                    }
+                    
+                    // calculate correct initial actual positions
+                    for (std::size_t i = 1; i < b; ++i)
+                    {
+                        this->actual_positions[i] += this->actual_positions[i - 1];
+                    }
+                }
+            }     
+            else
+            {
+                // find cell k such that heights[k-1] <= args[sample] < heights[k] and adjust extreme values
+                if (args[sample] < this->heights[0])
+                {
+                    this->heights[0] = args[sample];
+                    this->actual_positions[0] = args[weight];
+                    sample_cell = 1;
+                }
+                else if (this->heights[b] <= args[sample])
+                {
+                    this->heights[b] = args[sample];
+                    sample_cell = b;
+                }
+                else
+                {
+                    typename array_type::iterator it;
+                    it = std::upper_bound(
+                        this->heights.begin()
+                      , this->heights.end()
+                      , args[sample]
+                    );
+                                    
+                    sample_cell = std::distance(this->heights.begin(), it);
+                }
+                
+                // increment positions of markers above sample_cell
+                for (std::size_t i = sample_cell; i < b + 1; ++i)
+                {
+                    this->actual_positions[i] += args[weight];
+                }
+                
+                // determine desired marker positions
+                for (std::size_t i = 1; i < b + 1; ++i)
+                {
+                    this->desired_positions[i] = this->actual_positions[0]
+                                               + numeric::average((i-1) * (sum_of_weights(args) - this->actual_positions[0]), b);
+                }
+                
+                // adjust heights of markers 2 to num_cells if necessary
+                for (std::size_t i = 1; i < b; ++i)
+                {
+                    // offset to desire position
+                    float_type d = this->desired_positions[i] - this->actual_positions[i];
+                                        
+                    // offset to next position
+                    float_type dp = this->actual_positions[i + 1] - this->actual_positions[i];
+                    
+                    // offset to previous position
+                    float_type dm = this->actual_positions[i - 1] - this->actual_positions[i];
+                    
+                    // height ds
+                    float_type hp = (this->heights[i + 1] - this->heights[i]) / dp;
+                    float_type hm = (this->heights[i - 1] - this->heights[i]) / dm;
+                    
+                    if ( ( d >= 1. && dp > 1. ) || ( d <= -1. && dm < -1. ) )
+                    {
+                        short sign_d = static_cast<short>(d / std::abs(d));
+                                               
+                        // try adjusting heights[i] using p-squared formula
+                        float_type h = this->heights[i] + sign_d / (dp - dm) * ( (sign_d - dm) * hp + (dp - sign_d) * hm );
+                        
+                        if ( this->heights[i - 1] < h && h < this->heights[i + 1] )
+                        {
+                            this->heights[i] = h;
+                        }
+                        else
+                        {
+                            // use linear formula
+                            if (d>0)
+                            {
+                                this->heights[i] += hp;
+                            }
+                            if (d<0)
+                            {
+                                this->heights[i] -= hm;
+                            }
+                        }
+                        this->actual_positions[i] += sign_d;
+                    }
+                }
+            }
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            if (this->is_dirty)
+            {
+                this->is_dirty = false;
+            
+                // creates a vector of std::pair where each pair i holds
+                // the values heights[i] (x-axis of histogram) and
+                // actual_positions[i] / sum_of_weights (y-axis of histogram)
+                            
+                for (std::size_t i = 0; i < this->histogram.size(); ++i)
+                {
+                    this->histogram[i] = std::make_pair(this->heights[i], numeric::average(this->actual_positions[i], sum_of_weights(args)));
+                }
+            }
+            
+            return make_iterator_range(this->histogram);
+        }
+
+    private:
+        std::size_t num_cells;            // number of cells b
+        array_type  heights;              // q_i
+        array_type  actual_positions;     // n_i
+        array_type  desired_positions;    // n'_i
+        mutable histogram_type histogram; // histogram
+        mutable bool is_dirty;
+    };
+
+} // namespace detail
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_p_square_cumulative_distribution
+//
+namespace tag
+{
+    struct weighted_p_square_cumulative_distribution
+      : depends_on<count, sum_of_weights>
+      , p_square_cumulative_distribution_num_cells
+    {
+        typedef accumulators::impl::weighted_p_square_cumulative_distribution_impl<mpl::_1, mpl::_2> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_p_square_cumulative_distribution
+//
+namespace extract
+{
+    extractor<tag::weighted_p_square_cumulative_distribution> const weighted_p_square_cumulative_distribution = {};
+}
+
+using extract::weighted_p_square_cumulative_distribution;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_p_square_quantile.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_p_square_quantile.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,252 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_p_square_quantile.hpp
+//
+//  Copyright 2005 Daniel Egloff. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_P_SQUARE_QUANTILE_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_P_SQUARE_QUANTILE_HPP_DE_01_01_2006
+
+#include <functional>
+#include <boost/array.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/sum.hpp>
+#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl {
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_p_square_quantile_impl
+    //  single quantile estimation with weighted samples
+    /**
+        @brief Single quantile estimation with the \f$P^2\f$ algorithm for weighted samples
+
+        This version of the \f$P^2\f$ algorithm extends the \f$P^2\f$ algorithm to support weighted samples. 
+        The \f$P^2\f$ algorithm estimates a quantile dynamically without storing samples. Instead of
+        storing the whole sample cumulative distribution, only five points (markers) are stored. The heights 
+        of these markers are the minimum and the maximum of the samples and the current estimates of the 
+        \f$(p/2)\f$-, \f$p\f$ - and \f$(1+p)/2\f$ -quantiles. Their positions are equal to the number 
+        of samples that are smaller or equal to the markers. Each time a new sample is added, the 
+        positions of the markers are updated and if necessary their heights are adjusted using a piecewise-
+        parabolic formula.
+
+        For further details, see
+
+        R. Jain and I. Chlamtac, The P^2 algorithmus for dynamic calculation of quantiles and 
+        histograms without storing observations, Communications of the ACM,   
+        Volume 28 (October), Number 10, 1985, p. 1076-1085.
+
+        @param quantile_probability 
+    */
+    template<typename Sample, typename Weight, typename Impl>
+    struct weighted_p_square_quantile_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        typedef typename numeric::functional::average<weighted_sample, std::size_t>::result_type float_type;
+        typedef array<float_type, 5> array_type;
+        // for boost::result_of
+        typedef float_type result_type;
+        
+        template<typename Args>
+        weighted_p_square_quantile_impl(Args const &args)
+          : p(is_same<Impl, for_median>::value ? 0.5 : args[quantile_probability | 0.5]) 
+          , heights()
+          , actual_positions()
+          , desired_positions()
+        {
+        }
+        
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            std::size_t cnt = count(args);
+                      
+            // accumulate 5 first samples
+            if (cnt <= 5)
+            {
+                this->heights[cnt - 1] = args[sample];
+                
+                // In this initialization phase, actual_positions stores the weights of the
+                // inital samples that are needed at the end of the initialization phase to
+                // compute the correct initial positions of the markers.
+                this->actual_positions[cnt - 1] = args[weight];
+                
+                // complete the initialization of heights and actual_positions by sorting
+                if (cnt == 5)
+                {
+                    // TODO: we need to sort the initial samples (in heights) in ascending order and 
+                    // sort their weights (in actual_positions) the same way. The following lines do 
+                    // it, but there must be a better and more efficient way of doing this.
+                    typename array_type::iterator it_begin, it_end, it_min;
+                    
+                    it_begin = this->heights.begin();
+                    it_end   = this->heights.end();
+                    
+                    std::size_t pos = 0;
+                    
+                    while (it_begin != it_end)
+                    {
+                        it_min = std::min_element(it_begin, it_end);
+                        std::size_t d = std::distance(it_begin, it_min);
+                        std::swap(*it_begin, *it_min);
+                        std::swap(this->actual_positions[pos], this->actual_positions[pos + d]);
+                        ++it_begin;
+                        ++pos;
+                    }
+                    
+                    // calculate correct initial actual positions
+                    for (std::size_t i = 1; i < 5; ++i)
+                    {
+                        this->actual_positions[i] += this->actual_positions[i - 1];
+                    }
+                }
+            }
+            else
+            {
+                std::size_t sample_cell = 1; // k
+
+                // find cell k such that heights[k-1] <= args[sample] < heights[k] and adjust extreme values
+                if (args[sample] < this->heights[0])
+                {
+                    this->heights[0] = args[sample];
+                    this->actual_positions[0] = args[weight];
+                    sample_cell = 1;
+                }
+                else if (this->heights[4] <= args[sample])
+                {
+                    this->heights[4] = args[sample];
+                    sample_cell = 4;
+                }
+                else
+                {
+                    typedef typename array_type::iterator iterator;
+                    iterator it = std::upper_bound(
+                        this->heights.begin()
+                      , this->heights.end()
+                      , args[sample]
+                    );
+
+                    sample_cell = std::distance(this->heights.begin(), it);
+                }
+                
+                // increment positions of markers above sample_cell
+                for (std::size_t i = sample_cell; i < 5; ++i)
+                {
+                    this->actual_positions[i] += args[weight];
+                }
+                
+                // update desired positions for all markers
+                this->desired_positions[0] = this->actual_positions[0];
+                this->desired_positions[1] = (sum_of_weights(args) - this->actual_positions[0])
+                                           * this->p/2. + this->actual_positions[0];
+                this->desired_positions[2] = (sum_of_weights(args) - this->actual_positions[0])
+                                           * this->p + this->actual_positions[0];
+                this->desired_positions[3] = (sum_of_weights(args) - this->actual_positions[0])
+                                           * (1. + this->p)/2. + this->actual_positions[0];
+                this->desired_positions[4] = sum_of_weights(args);
+                                
+                // adjust height and actual positions of markers 1 to 3 if necessary
+                for (std::size_t i = 1; i <= 3; ++i)
+                {
+                    // offset to desired positions
+                    float_type d = this->desired_positions[i] - this->actual_positions[i];
+                    
+                    // offset to next position
+                    float_type dp = this->actual_positions[i + 1] - this->actual_positions[i];
+                    
+                    // offset to previous position
+                    float_type dm = this->actual_positions[i - 1] - this->actual_positions[i];
+                    
+                    // height ds
+                    float_type hp = (this->heights[i + 1] - this->heights[i]) / dp;
+                    float_type hm = (this->heights[i - 1] - this->heights[i]) / dm;
+                    
+                    if ( ( d >= 1. && dp > 1. ) || ( d <= -1. && dm < -1. ) )
+                    {
+                        short sign_d = static_cast<short>(d / std::abs(d));
+                                               
+                        // try adjusting heights[i] using p-squared formula
+                        float_type h = this->heights[i] + sign_d / (dp - dm) * ( (sign_d - dm) * hp + (dp - sign_d) * hm );
+                        
+                        if ( this->heights[i - 1] < h && h < this->heights[i + 1] )
+                        {
+                            this->heights[i] = h;
+                        }
+                        else
+                        {
+                            // use linear formula
+                            if (d>0)
+                            {
+                                this->heights[i] += hp;
+                            }
+                            if (d<0)
+                            {
+                                this->heights[i] -= hm;
+                            }
+                        }
+                        this->actual_positions[i] += sign_d;
+                    }
+                }
+            }
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return this->heights[2];
+        }
+
+    private:
+        float_type p;                    // the quantile probability p
+        array_type heights;              // q_i
+        array_type actual_positions;     // n_i
+        array_type desired_positions;    // n'_i
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_p_square_quantile
+//
+namespace tag
+{
+    struct weighted_p_square_quantile
+      : depends_on<count, sum_of_weights>
+    {
+        typedef accumulators::impl::weighted_p_square_quantile_impl<mpl::_1, mpl::_2, regular> impl;
+    };
+    struct weighted_p_square_quantile_for_median
+      : depends_on<count, sum_of_weights>
+    {
+        typedef accumulators::impl::weighted_p_square_quantile_impl<mpl::_1, mpl::_2, for_median> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_p_square_quantile
+// extract::weighted_p_square_quantile_for_median
+//
+namespace extract
+{
+    extractor<tag::weighted_p_square_quantile> const weighted_p_square_quantile = {};
+    extractor<tag::weighted_p_square_quantile_for_median> const weighted_p_square_quantile_for_median = {};
+}
+
+using extract::weighted_p_square_quantile;
+using extract::weighted_p_square_quantile_for_median;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_peaks_over_threshold.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_peaks_over_threshold.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,278 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_peaks_over_threshold.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_PEAKS_OVER_THRESHOLD_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_PEAKS_OVER_THRESHOLD_HPP_DE_01_01_2006
+
+#include <vector>
+#include <limits>
+#include <numeric>
+#include <functional>
+#include <boost/range.hpp>
+#include <boost/mpl/if.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/tuple/tuple.hpp>
+#include <boost/lambda/lambda.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
+#include <boost/accumulators/statistics/peaks_over_threshold.hpp> // for named parameters pot_threshold_value and pot_threshold_probability
+#include <boost/accumulators/statistics/sum.hpp>
+#include <boost/accumulators/statistics/tail_variate.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{      
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_peaks_over_threshold_impl
+    //  works with an explicit threshold value and does not depend on order statistics of weighted samples
+    /**
+        @brief Weighted Peaks over Threshold Method for Weighted Quantile and Weighted Tail Mean Estimation
+        
+        @sa peaks_over_threshold_impl
+
+        @param quantile_probability
+        @param pot_threshold_value
+    */
+    template<typename Sample, typename Weight, typename LeftRight>
+    struct weighted_peaks_over_threshold_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Weight, Sample>::result_type weighted_sample;
+        typedef typename numeric::functional::average<weighted_sample, std::size_t>::result_type float_type;
+        // for boost::result_of
+        typedef boost::tuple<float_type, float_type, float_type> result_type;
+        
+        template<typename Args>
+        weighted_peaks_over_threshold_impl(Args const &args)
+          : sign_((is_same<LeftRight, left>::value) ? -1 : 1)
+          , mu_(sign_ * numeric::average(args[sample | Sample()], (std::size_t)1))
+          , sigma2_(numeric::average(args[sample | Sample()], (std::size_t)1))
+          , w_sum_(numeric::average(args[weight | Weight()], (std::size_t)1))
+          , threshold_(sign_ * args[pot_threshold_value])
+          , fit_parameters_(boost::make_tuple(0., 0., 0.))
+          , is_dirty_(true)
+        {
+        }
+        
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            this->is_dirty_ = true;
+        
+            if (this->sign_ * args[sample] > this->threshold_)
+            {
+                this->mu_ += args[weight] * args[sample];
+                this->sigma2_ += args[weight] * args[sample] * args[sample];
+                this->w_sum_ += args[weight];
+            }
+        }
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            if (this->is_dirty_)
+            {
+                this->is_dirty_ = false;
+            
+                this->mu_ = this->sign_ * numeric::average(this->mu_, this->w_sum_);
+                this->sigma2_ = numeric::average(this->sigma2_, this->w_sum_);
+                this->sigma2_ -= this->mu_ * this->mu_;
+                
+                float_type threshold_probability = numeric::average(sum_of_weights(args) - this->w_sum_, sum_of_weights(args));
+                
+                float_type tmp = numeric::average(( this->mu_ - this->threshold_ )*( this->mu_ - this->threshold_ ), this->sigma2_);
+                float_type xi_hat = 0.5 * ( 1. - tmp );
+                float_type beta_hat = 0.5 * ( this->mu_ - this->threshold_ ) * ( 1. + tmp );
+                float_type beta_bar = beta_hat * std::pow(1. - threshold_probability, xi_hat);
+                float_type u_bar = this->threshold_ - beta_bar * ( std::pow(1. - threshold_probability, -xi_hat) - 1.)/xi_hat;
+                this->fit_parameters_ = boost::make_tuple(u_bar, beta_bar, xi_hat);
+            }
+                      
+            return this->fit_parameters_;
+        }
+
+    private:
+        short sign_;                         // for left tail fitting, mirror the extreme values
+        mutable float_type mu_;              // mean of samples above threshold
+        mutable float_type sigma2_;          // variance of samples above threshold
+        mutable float_type w_sum_;           // sum of weights of samples above threshold
+        float_type threshold_;
+        mutable result_type fit_parameters_; // boost::tuple that stores fit parameters
+        mutable bool is_dirty_;
+    };
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_peaks_over_threshold_prob_impl
+    //  determines threshold from a given threshold probability using order statistics
+    /**
+        @brief Peaks over Threshold Method for Quantile and Tail Mean Estimation
+
+        @sa weighted_peaks_over_threshold_impl
+        
+        @param quantile_probability
+        @param pot_threshold_probability
+    */
+    template<typename Sample, typename Weight, typename LeftRight>
+    struct weighted_peaks_over_threshold_prob_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Weight, Sample>::result_type weighted_sample;
+        typedef typename numeric::functional::average<weighted_sample, std::size_t>::result_type float_type;
+        // for boost::result_of
+        typedef boost::tuple<float_type, float_type, float_type> result_type;
+        
+        template<typename Args>
+        weighted_peaks_over_threshold_prob_impl(Args const &args)
+          : sign_((is_same<LeftRight, left>::value) ? -1 : 1)
+          , mu_(sign_ * numeric::average(args[sample | Sample()], (std::size_t)1))
+          , sigma2_(numeric::average(args[sample | Sample()], (std::size_t)1))
+          , threshold_probability_(args[pot_threshold_probability])
+          , fit_parameters_(boost::make_tuple(0., 0., 0.))
+          , is_dirty_(true)
+        {
+        }
+        
+        void operator ()(dont_care)
+        {
+            this->is_dirty_ = true;
+        }
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            if (this->is_dirty_)
+            {            
+                this->is_dirty_ = false;
+                
+                float_type threshold = sum_of_weights(args)
+                             * ( ( is_same<LeftRight, left>::value ) ? this->threshold_probability_ : 1. - this->threshold_probability_ );
+
+                std::size_t n = 0;
+                Weight sum = Weight(0);
+                
+                while (sum < threshold)
+                {
+                    if (n < tail_weights(args).size())
+                    {
+                        mu_ += *(tail_weights(args).begin() + n) * *(tail(args).begin() + n);
+                        sigma2_ += *(tail_weights(args).begin() + n) * *(tail(args).begin() + n) * (*(tail(args).begin() + n));
+                        sum += *(tail_weights(args).begin() + n);
+                        n++;
+                    }
+                    else
+                    {
+                        if (std::numeric_limits<float_type>::has_quiet_NaN)
+                        {
+                            return boost::make_tuple(
+                                std::numeric_limits<float_type>::quiet_NaN()
+                              , std::numeric_limits<float_type>::quiet_NaN()
+                              , std::numeric_limits<float_type>::quiet_NaN()
+                            );
+                        }
+                        else
+                        {
+                            std::ostringstream msg;
+                            msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")";
+                            boost::throw_exception(std::runtime_error(msg.str()));
+                            return boost::make_tuple(Sample(0), Sample(0), Sample(0));
+                        }
+                    }
+                }
+                
+                float_type u = *(tail(args).begin() + n - 1) * this->sign_;
+
+                
+                this->mu_ = this->sign_ * numeric::average(this->mu_, sum);
+                this->sigma2_ = numeric::average(this->sigma2_, sum);
+                this->sigma2_ -= this->mu_ * this->mu_;
+
+                if (is_same<LeftRight, left>::value)
+                    this->threshold_probability_ = 1. - this->threshold_probability_;
+                
+                float_type tmp = numeric::average(( this->mu_ - u )*( this->mu_ - u ), this->sigma2_);
+                float_type xi_hat = 0.5 * ( 1. - tmp );
+                float_type beta_hat = 0.5 * ( this->mu_ - u ) * ( 1. + tmp );
+                float_type beta_bar = beta_hat * std::pow(1. - threshold_probability_, xi_hat);
+                float_type u_bar = u - beta_bar * ( std::pow(1. - threshold_probability_, -xi_hat) - 1.)/xi_hat;
+                this->fit_parameters_ = boost::make_tuple(u_bar, beta_bar, xi_hat);
+
+            }
+            
+            return this->fit_parameters_;
+        }
+
+    private:
+        short sign_;                                // for left tail fitting, mirror the extreme values
+        mutable float_type mu_;                     // mean of samples above threshold u
+        mutable float_type sigma2_;                 // variance of samples above threshold u
+        mutable float_type threshold_probability_;
+        mutable result_type fit_parameters_;        // boost::tuple that stores fit parameters 
+        mutable bool is_dirty_;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_peaks_over_threshold
+//
+namespace tag
+{
+    template<typename LeftRight>
+    struct weighted_peaks_over_threshold
+      : depends_on<sum_of_weights>
+      , pot_threshold_value
+    {
+        /// INTERNAL ONLY
+        typedef accumulators::impl::weighted_peaks_over_threshold_impl<mpl::_1, mpl::_2, LeftRight> impl;
+    };
+    
+    template<typename LeftRight>
+    struct weighted_peaks_over_threshold_prob
+      : depends_on<sum_of_weights, tail_weights<LeftRight> >
+      , pot_threshold_probability
+    {
+        /// INTERNAL ONLY
+        typedef accumulators::impl::weighted_peaks_over_threshold_prob_impl<mpl::_1, mpl::_2, LeftRight> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_peaks_over_threshold
+//
+namespace extract
+{
+    extractor<tag::abstract_peaks_over_threshold> const weighted_peaks_over_threshold = {};
+}
+
+using extract::weighted_peaks_over_threshold;
+
+// weighted_peaks_over_threshold<LeftRight>(with_threshold_value) -> weighted_peaks_over_threshold<LeftRight>
+template<typename LeftRight>
+struct as_feature<tag::weighted_peaks_over_threshold<LeftRight>(with_threshold_value)>
+{
+    typedef tag::weighted_peaks_over_threshold<LeftRight> type;
+};
+
+// weighted_peaks_over_threshold<LeftRight>(with_threshold_probability) -> weighted_peaks_over_threshold_prob<LeftRight>
+template<typename LeftRight>
+struct as_feature<tag::weighted_peaks_over_threshold<LeftRight>(with_threshold_probability)>
+{
+    typedef tag::weighted_peaks_over_threshold_prob<LeftRight> type;
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_skewness.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_skewness.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,99 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_skewness.hpp
+//
+//  Copyright 2006 Olivier Gygi, Daniel Egloff. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_SKEWNESS_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_SKEWNESS_HPP_EAN_28_10_2005
+
+#include <limits>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/weighted_moment.hpp>
+#include <boost/accumulators/statistics/weighted_mean.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_skewness_impl
+    /**
+        @brief Skewness estimation for weighted samples
+
+        The skewness of a sample distribution is defined as the ratio of the 3rd central moment and the \f$ 3/2 \f$-th power $
+        of the 2nd central moment (the variance) of the samples. The skewness can also be expressed by the simple moments:
+        
+        \f[
+            \hat{g}_1 =
+                \frac
+                {\widehat{m}_n^{(3)}-3\widehat{m}_n^{(2)}\hat{\mu}_n+2\hat{\mu}_n^3}
+                {\left(\widehat{m}_n^{(2)} - \hat{\mu}_n^{2}\right)^{3/2}}
+        \f]
+        
+        where \f$ \widehat{m}_n^{(i)} \f$ are the \f$ i \f$-th moment and \f$ \hat{\mu}_n \f$ the mean (first moment) of the 
+        \f$ n \f$ samples.
+        
+        The skewness estimator for weighted samples is formally identical to the estimator for unweighted samples, except that 
+        the weighted counterparts of all measures it depends on are to be taken.
+    */
+    template<typename Sample, typename Weight>
+    struct weighted_skewness_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        // for boost::result_of
+        typedef typename numeric::functional::average<weighted_sample, weighted_sample>::result_type result_type;
+
+        weighted_skewness_impl(dont_care) {}
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return numeric::average(
+                        weighted_moment<3>(args) 
+                        - 3. * weighted_moment<2>(args) * weighted_mean(args)
+                        + 2. * weighted_mean(args) * weighted_mean(args) * weighted_mean(args)
+                      , ( weighted_moment<2>(args) - weighted_mean(args) * weighted_mean(args) ) 
+                      * std::sqrt( weighted_moment<2>(args) - weighted_mean(args) * weighted_mean(args) )
+                   );
+        }
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_skewness
+//
+namespace tag
+{
+    struct weighted_skewness
+      : depends_on<weighted_mean, weighted_moment<2>, weighted_moment<3> >
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::weighted_skewness_impl<mpl::_1, mpl::_2> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_skewness
+//
+namespace extract
+{
+    extractor<tag::weighted_skewness> const weighted_skewness = {};
+}
+
+using extract::weighted_skewness;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_sum.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_sum.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,113 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_sum.hpp
+//
+//  Copyright 2006 Eric Niebler, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_SUM_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_SUM_HPP_EAN_28_10_2005
+
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/parameters/weight.hpp>
+#include <boost/accumulators/framework/accumulators/external_accumulator.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_sum_impl
+    template<typename Sample, typename Weight, typename Tag>
+    struct weighted_sum_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        
+        // for boost::result_of
+        typedef weighted_sample result_type;
+
+        template<typename Args>
+        weighted_sum_impl(Args const &args)
+          : weighted_sum_(
+                args[parameter::keyword<Tag>::get() | Sample()]
+                  * numeric::one<Weight>::value
+            )
+        {
+        }
+        
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            // what about overflow?
+            this->weighted_sum_ += args[parameter::keyword<Tag>::get()] * args[weight];
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->weighted_sum_;
+        }
+
+    private:
+
+        weighted_sample weighted_sum_;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_sum
+//
+namespace tag
+{
+    struct weighted_sum
+      : depends_on<>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::weighted_sum_impl<mpl::_1, mpl::_2, tag::sample> impl;
+    };
+    
+    template<typename VariateType, typename VariateTag>
+    struct weighted_sum_of_variates
+      : depends_on<>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::weighted_sum_impl<VariateType, mpl::_2, VariateTag> impl;
+    };
+    
+    struct abstract_weighted_sum_of_variates
+      : depends_on<>
+    {
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_sum
+//
+namespace extract
+{
+    extractor<tag::weighted_sum> const weighted_sum = {};
+    extractor<tag::abstract_weighted_sum_of_variates> const weighted_sum_of_variates = {};
+}
+
+using extract::weighted_sum;
+using extract::weighted_sum_of_variates;
+
+template<typename VariateType, typename VariateTag>
+struct feature_of<tag::weighted_sum_of_variates<VariateType, VariateTag> >
+  : feature_of<tag::abstract_weighted_sum_of_variates>
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_tail_mean.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_tail_mean.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,158 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_tail_mean.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_TAIL_MEAN_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_TAIL_MEAN_HPP_DE_01_01_2006
+
+#include <numeric>
+#include <vector>
+#include <limits>
+#include <functional>
+#include <sstream>
+#include <stdexcept>
+#include <boost/throw_exception.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/tail.hpp>
+#include <boost/accumulators/statistics/tail_mean.hpp>
+#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+     
+    ///////////////////////////////////////////////////////////////////////////////
+    // coherent_weighted_tail_mean_impl
+    //
+    // TODO
+    
+    ///////////////////////////////////////////////////////////////////////////////
+    // non_coherent_weighted_tail_mean_impl
+    //       
+    /**
+        @brief Estimation of the (non-coherent) weighted tail mean based on order statistics (for both left and right tails)
+
+        
+        
+        An estimation of the non-coherent, weighted tail mean \f$\widehat{NCTM}_{n,\alpha}(X)\f$ is given by the weighted mean 
+        of the
+        
+        \f[
+            \lambda = \inf\left\{ l \left| \frac{1}{\bar{w}_n}\sum_{i=1}^{l} w_i \geq \alpha \right. \right\}
+        \f]
+        
+        smallest samples (left tail) or the weighted mean of the
+        
+        \f[
+            n + 1 - \rho = n + 1 - \sup\left\{ r \left| \frac{1}{\bar{w}_n}\sum_{i=r}^{n} w_i \geq (1 - \alpha) \right. \right\}
+        \f]
+        
+        largest samples (right tail) above a quantile \f$\hat{q}_{\alpha}\f$ of level \f$\alpha\f$, \f$n\f$ being the total number of sample 
+        and \f$\bar{w}_n\f$ the sum of all \f$n\f$ weights:
+        
+        \f[
+            \widehat{NCTM}_{n,\alpha}^{\mathrm{left}}(X) = \frac{\sum_{i=1}^{\lambda} w_i X_{i:n}}{\sum_{i=1}^{\lambda} w_i},
+        \f]
+        
+        \f[
+            \widehat{NCTM}_{n,\alpha}^{\mathrm{right}}(X) = \frac{\sum_{i=\rho}^n w_i X_{i:n}}{\sum_{i=\rho}^n w_i}.
+        \f]
+        
+        @param quantile_probability
+    */
+    template<typename Sample, typename Weight, typename LeftRight>
+    struct non_coherent_weighted_tail_mean_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        typedef typename numeric::functional::average<Weight, std::size_t>::result_type float_type;
+        // for boost::result_of
+        typedef typename numeric::functional::average<weighted_sample, std::size_t>::result_type result_type;
+        
+        non_coherent_weighted_tail_mean_impl(dont_care) {}
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            float_type threshold = sum_of_weights(args)
+                             * ( ( is_same<LeftRight, left>::value ) ? args[quantile_probability] : 1. - args[quantile_probability] );
+
+            std::size_t n = 0;
+            Weight sum = Weight(0);
+            
+            while (sum < threshold)
+            {
+                if (n < tail_weights(args).size())
+                {
+                    sum += *(tail_weights(args).begin() + n);
+                    n++;
+                }
+                else
+                {
+                    if (std::numeric_limits<result_type>::has_quiet_NaN)
+                    {
+                        return std::numeric_limits<result_type>::quiet_NaN();
+                    }
+                    else
+                    {
+                        std::ostringstream msg;
+                        msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")";
+                        boost::throw_exception(std::runtime_error(msg.str()));
+                        return result_type(0);
+                    }
+                }
+            }
+            
+            return numeric::average(
+                std::inner_product(
+                    tail(args).begin()
+                  , tail(args).begin() + n
+                  , tail_weights(args).begin()
+                  , weighted_sample(0)
+                )
+              , sum
+            );     
+        }
+    };
+
+} // namespace impl
+
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::non_coherent_weighted_tail_mean<>
+//
+namespace tag
+{
+    template<typename LeftRight>
+    struct non_coherent_weighted_tail_mean
+      : depends_on<sum_of_weights, tail_weights<LeftRight> >
+    {
+        typedef accumulators::impl::non_coherent_weighted_tail_mean_impl<mpl::_1, mpl::_2, LeftRight> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::non_coherent_weighted_tail_mean;
+//
+namespace extract
+{
+    extractor<tag::abstract_non_coherent_tail_mean> const non_coherent_weighted_tail_mean = {};
+}
+
+using extract::non_coherent_weighted_tail_mean;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_tail_quantile.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_tail_quantile.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,135 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_tail_quantile.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_TAIL_QUANTILE_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_TAIL_QUANTILE_HPP_DE_01_01_2006
+
+#include <vector>
+#include <limits>
+#include <functional>
+#include <sstream>
+#include <stdexcept>
+#include <boost/throw_exception.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/mpl/if.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/tail.hpp>
+#include <boost/accumulators/statistics/tail_quantile.hpp>
+#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{  
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_tail_quantile_impl
+    //  Tail quantile estimation based on order statistics of weighted samples
+    /**
+        @brief Tail quantile estimation based on order statistics of weighted samples (for both left and right tails)
+
+        An estimator \f$\hat{q}\f$ of tail quantiles with level \f$\alpha\f$ based on order statistics 
+        \f$X_{1:n} \leq X_{2:n} \leq\dots\leq X_{n:n}\f$ of weighted samples are given by \f$X_{\lambda:n}\f$ (left tail) 
+        and \f$X_{\rho:n}\f$ (right tail), where
+        
+            \f[
+                \lambda = \inf\left\{ l \left| \frac{1}{\bar{w}_n}\sum_{i=1}^{l} w_i \geq \alpha \right. \right\}
+            \f]
+        
+        and
+        
+            \f[
+                \rho = \sup\left\{ r \left| \frac{1}{\bar{w}_n}\sum_{i=r}^{n} w_i \geq (1 - \alpha) \right. \right\},
+            \f]
+            
+        \f$n\f$ being the number of samples and \f$\bar{w}_n\f$ the sum of all weights.
+                
+        @param quantile_probability
+    */
+    template<typename Sample, typename Weight, typename LeftRight>
+    struct weighted_tail_quantile_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Weight, std::size_t>::result_type float_type;
+        // for boost::result_of
+        typedef Sample result_type;
+        
+        weighted_tail_quantile_impl(dont_care) {}
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            float_type threshold = sum_of_weights(args)
+                             * ( ( is_same<LeftRight, left>::value ) ? args[quantile_probability] : 1. - args[quantile_probability] );
+
+            std::size_t n = 0;
+            Weight sum = Weight(0);
+            
+            while (sum < threshold)
+            {
+                if (n < tail_weights(args).size())
+                {
+                    sum += *(tail_weights(args).begin() + n);
+                    n++;
+                }
+                else
+                {
+                    if (std::numeric_limits<result_type>::has_quiet_NaN)
+                    {
+                        return std::numeric_limits<result_type>::quiet_NaN();
+                    }
+                    else
+                    {
+                        std::ostringstream msg;
+                        msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")";
+                        boost::throw_exception(std::runtime_error(msg.str()));
+                        return Sample(0);
+                    }
+                }
+            }
+            
+            // Note that the cached samples of the left are sorted in ascending order, 
+            // whereas the samples of the right tail are sorted in descending order
+            return *(boost::begin(tail(args)) + n - 1);
+        }
+    };
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_tail_quantile<>
+//
+namespace tag
+{
+    template<typename LeftRight>
+    struct weighted_tail_quantile
+      : depends_on<sum_of_weights, tail_weights<LeftRight> >
+    {
+        /// INTERNAL ONLY
+        typedef accumulators::impl::weighted_tail_quantile_impl<mpl::_1, mpl::_2, LeftRight> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_tail_quantile
+//
+namespace extract
+{
+    extractor<tag::quantile> const weighted_tail_quantile = {};
+}
+
+using extract::weighted_tail_quantile;
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_tail_variate_means.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_tail_variate_means.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,233 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_tail_variate_means.hpp
+//
+//  Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_TAIL_VARIATE_MEANS_HPP_DE_01_01_2006
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_TAIL_VARIATE_MEANS_HPP_DE_01_01_2006
+
+#include <numeric>
+#include <vector>
+#include <limits>
+#include <functional>
+#include <sstream>
+#include <stdexcept>
+#include <boost/throw_exception.hpp>
+#include <boost/lambda/lambda.hpp>
+#include <boost/parameter/keyword.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/type_traits/is_same.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/tail.hpp>
+#include <boost/accumulators/statistics/tail_variate.hpp>
+#include <boost/accumulators/statistics/tail_variate_means.hpp>
+#include <boost/accumulators/statistics/weighted_tail_mean.hpp>
+#include <boost/accumulators/statistics/parameters/quantile_probability.hpp>
+
+namespace boost
+{
+    // for _BinaryOperatrion2 in std::inner_product below
+    // mutliplies two values and promotes the result to double
+    namespace numeric { namespace functional
+    {
+        ///////////////////////////////////////////////////////////////////////////////
+        // numeric::functional::multiply_and_promote_to_double
+        template<typename T, typename U>
+        struct multiply_and_promote_to_double
+          : multiplies<T, double const>
+        {
+        };
+    }}
+}
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    /**
+        @brief Estimation of the absolute and relative weighted tail variate means (for both left and right tails)
+        
+        For all \f$j\f$-th variates associated to the 
+        
+        \f[
+            \lambda = \inf\left\{ l \left| \frac{1}{\bar{w}_n}\sum_{i=1}^{l} w_i \geq \alpha \right. \right\}
+        \f]
+        
+        smallest samples (left tail) or the weighted mean of the
+        
+        \f[
+            n + 1 - \rho = n + 1 - \sup\left\{ r \left| \frac{1}{\bar{w}_n}\sum_{i=r}^{n} w_i \geq (1 - \alpha) \right. \right\}
+        \f]
+        
+        largest samples (right tail), the absolute weighted tail means \f$\widehat{ATM}_{n,\alpha}(X, j)\f$ 
+        are computed and returned as an iterator range. Alternatively, the relative weighted tail means 
+        \f$\widehat{RTM}_{n,\alpha}(X, j)\f$ are returned, which are the absolute weighted tail means 
+        normalized with the weighted (non-coherent) sample tail mean \f$\widehat{NCTM}_{n,\alpha}(X)\f$.
+        
+        \f[
+            \widehat{ATM}_{n,\alpha}^{\mathrm{right}}(X, j) = 
+                \frac{1}{\sum_{i=\rho}^n w_i}
+                \sum_{i=\rho}^n w_i \xi_{j,i}
+        \f]
+        
+        \f[
+            \widehat{ATM}_{n,\alpha}^{\mathrm{left}}(X, j) = 
+                \frac{1}{\sum_{i=1}^{\lambda}}
+                \sum_{i=1}^{\lambda} w_i \xi_{j,i}
+        \f]
+        
+        \f[
+            \widehat{RTM}_{n,\alpha}^{\mathrm{right}}(X, j) = 
+                \frac{\sum_{i=\rho}^n w_i \xi_{j,i}}
+            {\sum_{i=\rho}^n w_i \widehat{NCTM}_{n,\alpha}^{\mathrm{right}}(X)}
+        \f]
+        
+        \f[
+            \widehat{RTM}_{n,\alpha}^{\mathrm{left}}(X, j) = 
+                \frac{\sum_{i=1}^{\lambda} w_i \xi_{j,i}}
+            {\sum_{i=1}^{\lambda} w_i \widehat{NCTM}_{n,\alpha}^{\mathrm{left}}(X)}
+        \f]
+    */
+    
+    ///////////////////////////////////////////////////////////////////////////////
+    // weighted_tail_variate_means_impl
+    //  by default: absolute weighted_tail_variate_means
+    template<typename Sample, typename Weight, typename Impl, typename LeftRight, typename VariateType>
+    struct weighted_tail_variate_means_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::average<Weight, Weight>::result_type float_type;
+        typedef typename numeric::functional::average<typename numeric::functional::multiplies<VariateType, Weight>::result_type, Weight>::result_type array_type;
+        // for boost::result_of
+        typedef iterator_range<typename array_type::iterator> result_type;
+        
+        weighted_tail_variate_means_impl(dont_care) {}
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            float_type threshold = sum_of_weights(args)
+                             * ( ( is_same<LeftRight, left>::value ) ? args[quantile_probability] : 1. - args[quantile_probability] );
+            
+            std::size_t n = 0;
+            Weight sum = Weight(0);
+            
+            while (sum < threshold)
+            {
+                if (n < tail_weights(args).size())
+                {
+                    sum += *(tail_weights(args).begin() + n);
+                    n++;
+                }
+                else
+                {
+                    if (std::numeric_limits<float_type>::has_quiet_NaN)
+                    {
+                        std::fill(
+                            this->tail_means_.begin()
+                          , this->tail_means_.end()
+                          , std::numeric_limits<float_type>::quiet_NaN()
+                        );
+                    }
+                    else
+                    {
+                        std::ostringstream msg;
+                        msg << "index n = " << n << " is not in valid range [0, " << tail(args).size() << ")";
+                        boost::throw_exception(std::runtime_error(msg.str()));
+                    }
+                }
+            }
+            
+            std::size_t num_variates = tail_variate(args).begin()->size();
+            
+            this->tail_means_.clear();
+            this->tail_means_.resize(num_variates, Sample(0));
+
+            this->tail_means_ = std::inner_product(
+                tail_variate(args).begin()
+              , tail_variate(args).begin() + n
+              , tail_weights(args).begin()
+              , this->tail_means_
+              , numeric::functional::plus<array_type const, array_type const>()
+              , numeric::functional::multiply_and_promote_to_double<VariateType const, Weight const>()
+            );
+            
+            float_type factor = sum * ( (is_same<Impl, relative>::value) ? non_coherent_weighted_tail_mean(args) : 1. );
+            
+            using boost::lambda::_1;
+            
+            std::transform(
+                this->tail_means_.begin()
+              , this->tail_means_.end()
+              , this->tail_means_.begin()
+              , _1 / factor
+            );           
+            
+            return make_iterator_range(this->tail_means_);
+        }
+
+    private:
+    
+        mutable array_type tail_means_;
+    
+    };
+    
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::absolute_weighted_tail_variate_means
+// tag::relative_weighted_tail_variate_means
+//
+namespace tag
+{
+    template<typename LeftRight, typename VariateType, typename VariateTag>
+    struct absolute_weighted_tail_variate_means
+      : depends_on<non_coherent_weighted_tail_mean<LeftRight>, tail_variate<VariateType, VariateTag, LeftRight>, tail_weights<LeftRight> >
+    {
+        typedef accumulators::impl::weighted_tail_variate_means_impl<mpl::_1, mpl::_2, absolute, LeftRight, VariateType> impl;
+    };
+    template<typename LeftRight, typename VariateType, typename VariateTag>  
+    struct relative_weighted_tail_variate_means
+      : depends_on<non_coherent_weighted_tail_mean<LeftRight>, tail_variate<VariateType, VariateTag, LeftRight>, tail_weights<LeftRight> >
+    {
+        typedef accumulators::impl::weighted_tail_variate_means_impl<mpl::_1, mpl::_2, relative, LeftRight, VariateType> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_tail_variate_means
+// extract::relative_weighted_tail_variate_means
+//
+namespace extract
+{
+    extractor<tag::abstract_absolute_tail_variate_means> const weighted_tail_variate_means = {};
+    extractor<tag::abstract_relative_tail_variate_means> const relative_weighted_tail_variate_means = {};
+}
+
+using extract::weighted_tail_variate_means;
+using extract::relative_weighted_tail_variate_means;
+
+// weighted_tail_variate_means<LeftRight, VariateType, VariateTag>(absolute) -> absolute_weighted_tail_variate_means<LeftRight, VariateType, VariateTag>
+template<typename LeftRight, typename VariateType, typename VariateTag>
+struct as_feature<tag::weighted_tail_variate_means<LeftRight, VariateType, VariateTag>(absolute)>
+{
+    typedef tag::absolute_weighted_tail_variate_means<LeftRight, VariateType, VariateTag> type;
+};
+
+// weighted_tail_variate_means<LeftRight, VariateType, VariateTag>(relative) -> relative_weighted_tail_variate_means<LeftRight, VariateType, VariateTag>
+template<typename LeftRight, typename VariateType, typename VariateTag>
+struct as_feature<tag::weighted_tail_variate_means<LeftRight, VariateType, VariateTag>(relative)>
+{
+    typedef tag::relative_weighted_tail_variate_means<LeftRight, VariateType, VariateTag> type;
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/weighted_variance.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/weighted_variance.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,184 @@
+///////////////////////////////////////////////////////////////////////////////
+// weighted_variance.hpp
+//
+//  Copyright 2005 Daniel Egloff, Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_VARIANCE_HPP_EAN_28_10_2005
+#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_VARIANCE_HPP_EAN_28_10_2005
+
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/framework/accumulator_base.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+#include <boost/accumulators/numeric/functional.hpp>
+#include <boost/accumulators/framework/parameters/sample.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+#include <boost/accumulators/statistics/variance.hpp>
+#include <boost/accumulators/statistics/weighted_sum.hpp>
+#include <boost/accumulators/statistics/weighted_mean.hpp>
+#include <boost/accumulators/statistics/weighted_moment.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace impl
+{
+    //! Lazy calculation of variance of weighted samples.
+    /*!
+        The default implementation of the variance of weighted samples is based on the second moment 
+        \f$\widehat{m}_n^{(2)}\f$ (weighted_moment<2>) and the mean\f$ \hat{\mu}_n\f$ (weighted_mean):
+        \f{
+            \hat{\sigma}_n^2 = \widehat{m}_n^{(2)}-\hat{\mu}_n^2,
+        \f]   
+        where \f$n\f$ is the number of samples.
+    */
+    template<typename Sample, typename Weight, typename MeanFeature>
+    struct weighted_variance_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        // for boost::result_of
+        typedef typename numeric::functional::average<weighted_sample, Weight>::result_type result_type;
+
+        weighted_variance_impl(dont_care) {}
+        
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            extractor<MeanFeature> const some_mean = {};
+            result_type tmp = some_mean(args);
+            return weighted_moment<2>(args) - tmp * tmp;
+        }
+    };
+
+    //! Iterative calculation of variance of weighted samples.
+    /*!
+        Iterative calculation of variance of weighted samples:
+        \f[
+            \hat{\sigma}_n^2 = 
+                \frac{\bar{w}_n - w_n}{\bar{w}_n}\hat{\sigma}_{n - 1}^2 
+              + \frac{w_n}{\bar{w}_n - w_n}\left(X_n - \hat{\mu}_n\right)^2
+            ,\quad n\ge2,\quad\hat{\sigma}_0^2 = 0.
+        \f]
+        where \f$\bar{w}_n\f$ is the sum of the \f$n\f$ weights \f$w_i\f$ and \f$\hat{\mu}_n\f$ 
+        the estimate of the mean of the weighted smaples. Note that the sample variance is not defined for 
+        \f$n <= 1\f$.
+    */
+    template<typename Sample, typename Weight, typename MeanFeature, typename Tag>
+    struct immediate_weighted_variance_impl
+      : accumulator_base
+    {
+        typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample;
+        // for boost::result_of
+        typedef typename numeric::functional::average<weighted_sample, Weight>::result_type result_type;
+
+        template<typename Args>
+        immediate_weighted_variance_impl(Args const &args)
+          : weighted_variance(numeric::average(args[sample | Sample()], numeric::one<Weight>::value))
+        {
+        }
+
+        template<typename Args>
+        void operator ()(Args const &args)
+        {
+            std::size_t cnt = count(args);
+                        
+            if(cnt > 1)
+            {
+                extractor<MeanFeature> const some_mean = {};
+                                
+                result_type tmp = args[parameter::keyword<Tag>::get()] - some_mean(args);
+                
+                this->weighted_variance =
+                    numeric::average(this->weighted_variance * (sum_of_weights(args) - args[weight]), sum_of_weights(args))
+                  + numeric::average(tmp * tmp * args[weight], sum_of_weights(args) - args[weight] );
+            }
+        }
+
+        result_type result(dont_care) const
+        {
+            return this->weighted_variance;
+        }
+
+    private:
+        result_type weighted_variance;
+    };
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// tag::weighted_variance
+// tag::immediate_weighted_variance
+//
+namespace tag
+{
+    struct weighted_variance
+      : depends_on<weighted_moment<2>, weighted_mean>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::weighted_variance_impl<mpl::_1, mpl::_2, weighted_mean> impl;
+    };
+    struct immediate_weighted_variance
+      : depends_on<count, immediate_weighted_mean>
+    {
+        /// INTERNAL ONLY
+        ///
+        typedef accumulators::impl::immediate_weighted_variance_impl<mpl::_1, mpl::_2, immediate_weighted_mean, sample> impl;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// extract::weighted_variance
+// extract::immediate_weighted_variance
+//
+namespace extract
+{
+    extractor<tag::weighted_variance> const weighted_variance = {};
+    extractor<tag::immediate_weighted_variance> const immediate_weighted_variance = {};
+}
+
+using extract::weighted_variance;
+using extract::immediate_weighted_variance;
+
+// weighted_variance(lazy) -> weighted_variance
+template<>
+struct as_feature<tag::weighted_variance(lazy)>
+{
+    typedef tag::weighted_variance type;
+};
+
+// weighted_variance(immediate) -> immediate_weighted_variance
+template<>
+struct as_feature<tag::weighted_variance(immediate)>
+{
+    typedef tag::immediate_weighted_variance type;
+};
+
+////////////////////////////////////////////////////////////////////////////
+//// droppable_accumulator<weighted_variance_impl>
+////  need to specialize droppable lazy weighted_variance to cache the result at the
+////  point the accumulator is dropped.
+///// INTERNAL ONLY
+/////
+//template<typename Sample, typename Weight, typename MeanFeature>
+//struct droppable_accumulator<impl::weighted_variance_impl<Sample, Weight, MeanFeature> >
+//  : droppable_accumulator_base<
+//        with_cached_result<impl::weighted_variance_impl<Sample, Weight, MeanFeature> >
+//    >
+//{
+//    template<typename Args>
+//    droppable_accumulator(Args const &args)
+//      : droppable_accumulator_base<
+//            with_cached_result<impl::weighted_variance_impl<Sample, Weight, MeanFeature> >
+//        >(args)
+//    {
+//    }
+//};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics/with_error.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics/with_error.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,44 @@
+///////////////////////////////////////////////////////////////////////////////
+// with_error.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_WITH_ERROR_HPP_EAN_01_11_2005
+#define BOOST_ACCUMULATORS_STATISTICS_WITH_ERROR_HPP_EAN_01_11_2005
+
+#include <boost/preprocessor/repetition/enum_params.hpp>
+#include <boost/mpl/vector.hpp>
+#include <boost/mpl/transform_view.hpp>
+#include <boost/mpl/placeholders.hpp>
+#include <boost/accumulators/statistics_fwd.hpp>
+#include <boost/accumulators/statistics/error_of.hpp>
+
+namespace boost { namespace accumulators
+{
+
+namespace detail
+{
+    template<typename Feature>
+    struct error_of_tag
+    {
+        typedef tag::error_of<Feature> type;
+    };
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// with_error
+//
+template<BOOST_PP_ENUM_PARAMS(BOOST_ACCUMULATORS_MAX_FEATURES, typename Feature)>
+struct with_error
+  : mpl::transform_view<
+        mpl::vector<BOOST_PP_ENUM_PARAMS(BOOST_ACCUMULATORS_MAX_FEATURES, Feature)>
+      , detail::error_of_tag<mpl::_1>
+    >
+{
+};
+
+}} // namespace boost::accumulators
+
+#endif

Added: trunk/boost/accumulators/statistics_fwd.hpp
==============================================================================
--- (empty file)
+++ trunk/boost/accumulators/statistics_fwd.hpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,397 @@
+///////////////////////////////////////////////////////////////////////////////
+// statistics_fwd.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_ACCUMULATORS_STATISTICS_STATISTICS_FWD_HPP_EAN_23_11_2005
+#define BOOST_ACCUMULATORS_STATISTICS_STATISTICS_FWD_HPP_EAN_23_11_2005
+
+#include <boost/mpl/apply_fwd.hpp> // for mpl::na
+#include <boost/mpl/print.hpp>
+#include <boost/preprocessor/repetition/enum_params_with_a_default.hpp>
+#include <boost/accumulators/accumulators_fwd.hpp>
+#include <boost/accumulators/framework/depends_on.hpp>
+#include <boost/accumulators/framework/extractor.hpp>
+
+namespace boost { namespace accumulators
+{
+
+///////////////////////////////////////////////////////////////////////////////
+// base struct and base extractor for quantiles
+namespace tag
+{
+    struct quantile
+      : depends_on<>
+    {
+        typedef mpl::print<class ____MISSING_SPECIFIC_QUANTILE_FEATURE_IN_ACCUMULATOR_SET____ > impl;
+    };
+}
+namespace extract
+{
+    extractor<tag::quantile> const quantile = {};
+}
+using extract::quantile;
+
+///////////////////////////////////////////////////////////////////////////////
+// base struct and base extractor for *coherent* tail means
+namespace tag
+{
+    struct tail_mean
+      : depends_on<>
+    {
+        typedef mpl::print<class ____MISSING_SPECIFIC_TAIL_MEAN_FEATURE_IN_ACCUMULATOR_SET____ > impl;
+    };
+}
+namespace extract
+{
+    extractor<tag::tail_mean> const tail_mean = {};
+}
+using extract::tail_mean;
+
+namespace tag
+{   
+    ///////////////////////////////////////////////////////////////////////////////
+    // Variates tags
+    struct weights;
+    struct covariate1;
+    struct covariate2;
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // Statistic tags
+    struct count;
+    template<typename VariateType, typename VariateTag>
+    struct covariance;
+    struct density;
+    template<typename Feature>
+    struct error_of;
+    struct extended_p_square;
+    struct extended_p_square_quantile;
+    struct extended_p_square_quantile_quadratic;
+    struct kurtosis;
+    struct max;
+    struct mean;
+    struct immediate_mean;
+    struct mean_of_weights;
+    struct immediate_mean_of_weights;
+    template<typename VariateType, typename VariateTag>
+    struct mean_of_variates;
+    template<typename VariateType, typename VariateTag>
+    struct immediate_mean_of_variates;
+    struct median;
+    struct with_density_median;
+    struct with_p_square_cumulative_distribution_median;
+    struct min;
+    template<int N>
+    struct moment;
+    template<typename LeftRight>
+    struct peaks_over_threshold;
+    template<typename LeftRight>
+    struct peaks_over_threshold_prob;
+    template<typename LeftRight>
+    struct pot_tail_mean;
+    template<typename LeftRight>
+    struct pot_tail_mean_prob;
+    template<typename LeftRight>
+    struct pot_quantile;
+    template<typename LeftRight>
+    struct pot_quantile_prob;
+    struct p_square_cumulative_distribution;
+    struct p_square_quantile;
+    struct p_square_quantile_for_median;
+    struct skewness;
+    struct sum;
+    struct sum_of_weights;
+    template<typename VariateType, typename VariateTag>
+    struct sum_of_variates;
+    template<typename LeftRight>
+    struct tail;
+    template<typename LeftRight>
+    struct coherent_tail_mean;
+    template<typename LeftRight>
+    struct non_coherent_tail_mean;
+    template<typename LeftRight>
+    struct tail_quantile;
+    template<typename VariateType, typename VariateTag, typename LeftRight>
+    struct tail_variate;
+    template<typename LeftRight>
+    struct tail_weights;
+    template<typename VariateType, typename VariateTag, typename LeftRight>
+    struct right_tail_variate;
+    template<typename VariateType, typename VariateTag, typename LeftRight>
+    struct left_tail_variate;
+    template<typename LeftRight, typename VariateType, typename VariateTag>  
+    struct tail_variate_means;
+    template<typename LeftRight, typename VariateType, typename VariateTag>
+    struct absolute_tail_variate_means;
+    template<typename LeftRight, typename VariateType, typename VariateTag>
+    struct relative_tail_variate_means;
+    struct variance;
+    struct immediate_variance;
+    template<typename VariateType, typename VariateTag>
+    struct weighted_covariance;
+    struct weighted_density;
+    struct weighted_kurtosis;
+    struct weighted_mean;
+    struct immediate_weighted_mean; 
+    template<typename VariateType, typename VariateTag>
+    struct weighted_mean_of_variates;
+    template<typename VariateType, typename VariateTag>
+    struct immediate_weighted_mean_of_variates;
+    struct weighted_median;
+    struct with_density_weighted_median;
+    struct with_p_square_cumulative_distribution_weighted_median;
+    struct weighted_extended_p_square;
+    struct weighted_extended_p_square_quantile;
+    struct weighted_extended_p_square_quantile_quadratic;
+    template<int N>
+    struct weighted_moment;
+    template<typename LeftRight>
+    struct weighted_peaks_over_threshold;
+    template<typename LeftRight>
+    struct weighted_peaks_over_threshold_prob;
+    template<typename LeftRight>
+    struct weighted_pot_quantile;
+    template<typename LeftRight>
+    struct weighted_pot_quantile_prob;
+    template<typename LeftRight>
+    struct weighted_pot_tail_mean;
+    template<typename LeftRight>
+    struct weighted_pot_tail_mean_prob;
+    struct weighted_p_square_cumulative_distribution;
+    struct weighted_p_square_quantile;
+    struct weighted_p_square_quantile_for_median;
+    struct weighted_skewness;
+    template<typename LeftRight>
+    struct weighted_tail_quantile;
+    template<typename LeftRight>
+    struct non_coherent_weighted_tail_mean;
+    template<typename LeftRight>
+    struct weighted_tail_quantile;
+    template<typename LeftRight, typename VariateType, typename VariateTag>
+    struct weighted_tail_variate_means;
+    template<typename LeftRight, typename VariateType, typename VariateTag>
+    struct absolute_weighted_tail_variate_means;
+    template<typename LeftRight, typename VariateType, typename VariateTag>
+    struct relative_weighted_tail_variate_means;
+    struct weighted_variance;
+    struct immediate_weighted_variance;
+    struct weighted_sum;
+    template<typename VariateType, typename VariateTag>
+    struct weighted_sum_of_variates;
+} // namespace tag
+
+namespace impl
+{
+    ///////////////////////////////////////////////////////////////////////////////
+    // Statistics impls
+    struct count_impl;
+    
+    template<typename Sample, typename VariateType, typename VariateTag>
+    struct covariance_impl;
+
+    template<typename Sample>
+    struct density_impl;
+    
+    template<typename Sample, typename Feature>
+    struct error_of_impl;
+
+    template<typename Sample, typename Variance>
+    struct error_of_mean_impl;
+    
+    template<typename Sample>
+    struct extended_p_square_impl;
+    
+    template<typename Sample, typename Impl1, typename Impl2>
+    struct extended_p_square_quantile_impl;
+    
+    template<typename Sample>
+    struct kurtosis_impl;
+    
+    template<typename Sample>
+    struct max_impl;
+
+    template<typename Sample>
+    struct median_impl;
+
+    template<typename Sample>
+    struct with_density_median_impl;
+
+    template<typename Sample>
+    struct with_p_square_cumulative_distribution_median_impl;
+       
+    template<typename Sample>
+    struct min_impl;
+
+    template<typename Sample, typename SumFeature = tag::sum>
+    struct mean_impl;
+
+    template<typename Sample, typename Tag = tag::sample>
+    struct immediate_mean_impl;
+
+    template<typename N, typename Sample>
+    struct moment_impl;
+    
+    template<typename Sample, typename LeftRight>
+    struct peaks_over_threshold_prob_impl;
+    
+    template<typename Sample, typename Impl, typename LeftRight>
+    struct pot_quantile_impl;
+
+    template<typename Sample, typename Impl, typename LeftRight>
+    struct pot_tail_mean_impl;
+    
+    template<typename Sample>
+    struct p_square_cumulative_distribution_impl;
+
+    template<typename Sample, typename Impl>
+    struct p_square_quantile_impl;
+
+    template<typename Sample>
+    struct skewness_impl;
+        
+    template<typename Sample, typename Tag = tag::sample>
+    struct sum_impl;
+    
+    template<typename Sample, typename LeftRight>
+    struct tail_impl;
+    
+    template<typename Sample, typename LeftRight>
+    struct coherent_tail_mean_impl;
+
+    template<typename Sample, typename LeftRight>
+    struct non_coherent_tail_mean_impl;
+    
+    template<typename Sample, typename LeftRight>
+    struct tail_quantile_impl;
+
+    template<typename VariateType, typename VariateTag, typename LeftRight>
+    struct tail_variate_impl;
+      
+    template<typename Sample, typename Impl, typename LeftRight, typename VariateTag>
+    struct tail_variate_means_impl;
+    
+    template<typename Sample, typename MeanFeature>
+    struct variance_impl;
+
+    template<typename Sample, typename MeanFeature, typename Tag>
+    struct immediate_variance_impl;
+    
+    template<typename Sample, typename Weight, typename VariateType, typename VariateTag>
+    struct weighted_covariance_impl;
+    
+    template<typename Sample, typename Weight>
+    struct weighted_density_impl;
+
+    template<typename Sample, typename Weight>
+    struct weighted_kurtosis_impl;
+
+    template<typename Sample>
+    struct weighted_median_impl;
+
+    template<typename Sample>
+    struct with_density_weighted_median_impl;
+
+    template<typename Sample, typename Weight>
+    struct with_p_square_cumulative_distribution_weighted_median_impl; 
+
+    template<typename Sample, typename Weight, typename Tag>
+    struct weighted_mean_impl;
+
+    template<typename Sample, typename Weight, typename Tag>
+    struct immediate_weighted_mean_impl;
+        
+    template<typename Sample, typename Weight, typename LeftRight>
+    struct weighted_peaks_over_threshold_impl;
+    
+    template<typename Sample, typename Weight, typename LeftRight>
+    struct weighted_peaks_over_threshold_prob_impl;    
+    
+    template<typename Sample, typename Weight>
+    struct with_p_square_cumulative_distribution_weighted_median_impl; 
+
+    template<typename Sample, typename Weight>
+    struct weighted_extended_p_square_impl;
+
+    template<typename N, typename Sample, typename Weight>
+    struct weighted_moment_impl;
+
+    template<typename Sample, typename Weight>
+    struct weighted_p_square_cumulative_distribution_impl;
+
+    template<typename Sample, typename Weight, typename Impl>
+    struct weighted_p_square_quantile_impl;
+
+    template<typename Sample, typename Weight>
+    struct weighted_skewness_impl;
+
+    template<typename Sample, typename Weight, typename Tag>
+    struct weighted_sum_impl;
+    
+    template<typename Sample, typename Weight, typename LeftRight>
+    struct non_coherent_weighted_tail_mean_impl;
+    
+    template<typename Sample, typename Weight, typename LeftRight>
+    struct weighted_tail_quantile_impl;
+    
+    template<typename Sample, typename Weight, typename Impl, typename LeftRight, typename VariateType>
+    struct weighted_tail_variate_means_impl;
+    
+    template<typename Sample, typename Weight, typename MeanFeature>
+    struct weighted_variance_impl;
+
+    template<typename Sample, typename Weight, typename MeanFeature, typename Tag>
+    struct immediate_weighted_variance_impl;
+
+
+} // namespace impl
+
+///////////////////////////////////////////////////////////////////////////////
+// stats
+//      A more descriptive name for an MPL sequence of statistics.
+template<BOOST_PP_ENUM_PARAMS_WITH_A_DEFAULT(BOOST_ACCUMULATORS_MAX_FEATURES, typename Feature, mpl::na)>
+struct stats;
+
+template<BOOST_PP_ENUM_PARAMS_WITH_A_DEFAULT(BOOST_ACCUMULATORS_MAX_FEATURES, typename Feature, mpl::na)>
+struct with_error;
+
+// modifiers for the mean and variance stats
+struct lazy {};
+struct immediate {};
+
+// modifiers for the variance stat
+// struct fast {};
+// struct accurate {};
+
+// modifiers for order
+struct right {};
+struct left {};
+// typedef right default_order_tag_type;
+
+// modifiers for the tail_variate_means stat
+struct absolute {};
+struct relative {};
+
+// modifiers for median and weighted_median stats
+struct with_density {};
+struct with_p_square_cumulative_distribution {};
+struct with_p_square_quantile {};
+
+// modifiers for peaks_over_threshold stat
+struct with_threshold_value {};
+struct with_threshold_probability {};
+
+// modifiers for extended_p_square_quantile and weighted_extended_p_square_quantile stats
+struct weighted {};
+struct unweighted {};
+struct linear {};
+struct quadratic {};
+
+// modifiers for p_square_quantile
+struct regular {};
+struct for_median {};
+
+}} // namespace boost::accumulators
+
+#endif

Modified: trunk/doc/Jamfile.v2
==============================================================================
--- trunk/doc/Jamfile.v2	(original)
+++ trunk/doc/Jamfile.v2	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -12,6 +12,10 @@
     :
     ## Build the various generated docs (Doxygen and QuickBook)...
 
+    <dependency>../libs/accumulators/doc//accdoc.xml
+    <dependency>../libs/accumulators/doc//statsdoc.xml
+    <dependency>../libs/accumulators/doc//opdoc.xml
+    <dependency>../libs/accumulators/doc//accumulators
     <dependency>../libs/program_options/doc//autodoc.xml
     <dependency>../libs/algorithm/string/doc//autodoc.xml
     <dependency>../libs/logic/doc//reference.xml
@@ -38,6 +42,7 @@
 
     ## Add path references to the QuickBook generated docs...
 
+    <implicit-dependency>../libs/accumulators/doc//accumulators
     <implicit-dependency>../libs/functional/hash/doc//hash
     #<implicit-dependency>../libs/type_traits/doc//type_traits
     <implicit-dependency>../libs/static_assert/doc//static_assert

Modified: trunk/doc/src/boost.xml
==============================================================================
--- trunk/doc/src/boost.xml	(original)
+++ trunk/doc/src/boost.xml	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -49,6 +49,8 @@
   <part id="libraries">
     <title>The Boost C++ Libraries (BoostBook Subset)</title>
 
+    <xi:include href="accumulators.xml"/>
+
     <xi:include href="../../libs/any/doc/any.xml"/>
     <xi:include href="../../libs/array/doc/array.xml"/>
 

Added: trunk/libs/accumulators/doc/Jamfile.v2
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/doc/Jamfile.v2	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,141 @@
+# Copyright Eric Niebler 2005. Use, modification, and distribution are
+# subject to the Boost Software License, Version 1.0. (See accompanying
+# file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+import doxygen ;
+import quickbook ;
+
+# Use Doxygen to emimt a tagfile with the definition of depends_on<>.
+# That tagfile will be used by Doxygen below when generating the Statistics
+# Library Reference. This is all so that the Doxygen-generated documentation
+# for the features shows the dependency relationships between them.
+doxygen tagfile
+    :
+        ../../../boost/accumulators/framework/depends_on.hpp
+        ../../../boost/accumulators/framework/extractor.hpp
+    :
+        <doxygen:param>MACRO_EXPANSION=YES
+        <doxygen:param>EXPAND_ONLY_PREDEF=YES
+        <doxygen:param>GENERATE_TAGFILE=accumulators.tag
+        <doxygen:param>"PREDEFINED=\"BOOST_ACCUMULATORS_DOXYGEN_INVOKED=1\" \\
+                                   \"BOOST_PP_REPEAT_FROM_TO(a,b,c,d)=\" \\
+                                   \"BOOST_PP_ENUM_PARAMS(a,b)=b ## 1, b ## 2, ...\""
+    ;
+
+doxygen accdoc
+    :
+        [ glob ../../../boost/accumulators/accumulators*.hpp ]
+        [ glob ../../../boost/accumulators/framework/*.hpp ]
+        [ glob ../../../boost/accumulators/framework/parameters/*.hpp ]
+        [ glob ../../../boost/accumulators/framework/accumulators/*.hpp ]
+    :
+        <doxygen:param>EXTRACT_ALL=YES
+        <doxygen:param>"PREDEFINED=\"BOOST_ACCUMULATORS_DOXYGEN_INVOKED=1\" \\
+                                   \"BOOST_PP_REPEAT_FROM_TO(a,b,c,d)=\" \\
+                                   \"BOOST_PP_REPEAT(a,b,c)=\" \\
+                                   \"BOOST_PARAMETER_KEYWORD(a,b)=\\
+                                         namespace a { struct b {}; } \\
+                                         boost::parameter::keyword<a::b> const b;\" \\
+                                   \"BOOST_PP_ENUM_PARAMS(a,b)=b ## 1, b ## 2, ...\""
+        <doxygen:param>HIDE_UNDOC_MEMBERS=NO
+        <doxygen:param>EXTRACT_PRIVATE=NO
+        <doxygen:param>ENABLE_PREPROCESSING=YES
+        <doxygen:param>MACRO_EXPANSION=YES
+        <doxygen:param>EXPAND_ONLY_PREDEF=YES
+        <doxygen:param>SEARCH_INCLUDES=NO
+        <reftitle>"Accumulators Framework Reference"
+    ;
+
+doxygen statsdoc
+    :
+        [ glob ../../../boost/accumulators/statistics*.hpp ]
+        [ glob ../../../boost/accumulators/statistics/*.hpp ]
+        [ glob ../../../boost/accumulators/statistics/variates/*.hpp ]
+    :
+        <doxygen:param>EXTRACT_ALL=YES
+        <doxygen:param>"PREDEFINED=\"BOOST_ACCUMULATORS_DOXYGEN_INVOKED=1\" \\
+                                   \"BOOST_PP_REPEAT_FROM_TO(a,b,c,d)=\" \\
+                                   \"BOOST_PP_REPEAT(a,b,c)=\" \\
+                                   \"BOOST_PARAMETER_KEYWORD(a,b)=\\
+                                         namespace a { struct b {}; } \\
+                                         boost::parameter::keyword<a::b> const b;\" \\
+                                   \"BOOST_PP_ENUM_PARAMS(a,b)=b ## 1, b ## 2, ...\""
+        <doxygen:param>HIDE_UNDOC_MEMBERS=NO
+        <doxygen:param>EXTRACT_PRIVATE=NO
+        <doxygen:param>ENABLE_PREPROCESSING=YES
+        <doxygen:param>MACRO_EXPANSION=YES
+        <doxygen:param>EXPAND_ONLY_PREDEF=YES
+        <doxygen:param>SEARCH_INCLUDES=NO
+        <doxygen:param>TAGFILES=accumulators.tag
+        <reftitle>"Statistics Library Reference"
+        <dependency>tagfile
+    ;
+
+doxygen opdoc
+    :
+        [ glob ../../../boost/accumulators/numeric/functional.hpp ]
+        [ glob ../../../boost/accumulators/numeric/functional/*.hpp ]
+    :
+        <doxygen:param>EXTRACT_ALL=YES
+        <doxygen:param>"PREDEFINED=\"BOOST_NUMERIC_FUNCTIONAL_DOXYGEN_INVOKED=1\" \\
+                                   \"BOOST_NUMERIC_FUNCTIONAL_DEFINE_BINARY_OP(a,b,c)=\\
+                                         namespace functional { \\
+                                         template<class Left,class Right,class EnableIf=void> struct a ## _base \\
+                                         : std::binary_function<Left, Right, typeof(lvalue<Left>() b lvalue<Right>())> { \\
+                                         /** \\return left b right */ \\
+                                         result_type operator()(Left &left, Right &right) const; }; \\
+                                         template<class Left,class Right, \\
+                                                  class LeftTag=typename tag<Left>::type, \\
+                                                  class RightTag=typename tag<Right>::type> \\
+                                         struct a : a ## _base<Left,Right,void> {}; } \\
+                                         namespace op { \\
+                                         struct a : boost::detail::function2< \\
+                                             functional::a<_1,_2,functional::tag<_1>,functional::tag<_2> > > {}; } \\
+                                         namespace { \\
+                                         /** \\return functional::a<Left, Right>()(left, right) */ \\
+                                         op::a const & a = boost::detail::pod_singleton<op::min_assign>::instance; } \" \\
+                                   \"BOOST_NUMERIC_FUNCTIONAL_DEFINE_UNARY_OP(a,b)=\\
+                                         namespace functional { \\
+                                         template<class Arg,class EnableIf=void> struct a ## _base \\
+                                         : std::unary_function<Arg, typeof(b lvalue<Arg>())> { \\
+                                         /** \\return b arg */ \\
+                                         result_type operator()(Arg & arg) const; }; \\
+                                         template<class Arg,class Tag=typename tag<Arg>::type> \\
+                                         struct a : a ## _base<Arg,void> {}; } \\
+                                         namespace op { \\
+                                         struct a : boost::detail::function1< \\
+                                             functional::a<_,functional::tag<_> > > {}; } \\
+                                         namespace { \\
+                                         /** \\return functional::a<Arg>()(arg) */ \\
+                                         op::a const & a = boost::detail::pod_singleton<op::min_assign>::instance; }\""
+        <doxygen:param>HIDE_UNDOC_MEMBERS=NO
+        <doxygen:param>EXTRACT_PRIVATE=NO
+        <doxygen:param>ENABLE_PREPROCESSING=YES
+        <doxygen:param>MACRO_EXPANSION=YES
+        <doxygen:param>EXPAND_ONLY_PREDEF=YES
+        <doxygen:param>SEARCH_INCLUDES=NO
+        <reftitle>"Numeric Operators Library Reference"
+    ;
+
+xml accumulators
+    :
+        accumulators.qbk
+    :
+        <xsl:param>boost.max.id.length=1024
+        <xsl:param>toc.max.depth=4
+        <xsl:param>toc.section.depth=4
+        <xsl:param>chunk.section.depth=2
+        <dependency>accdoc
+        <dependency>statsdoc
+        <dependency>opdoc
+    ;
+
+boostbook standalone
+    :
+        accumulators
+    :
+        <xsl:param>boost.max.id.length=1024
+        <xsl:param>toc.max.depth=4
+        <xsl:param>toc.section.depth=4
+        <xsl:param>chunk.section.depth=2
+    ;

Added: trunk/libs/accumulators/doc/accumulators.qbk
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/doc/accumulators.qbk	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,3190 @@
+
+[library Boost.Accumulators
+    [quickbook 1.3]
+    [authors [Niebler, Eric]]
+    [copyright 2005 2006 Eric Niebler]
+    [category math]
+    [id accumulators]
+    [dirname accumulators]
+    [purpose 
+        Incremental accumulation framework and statistical accumulator library.
+    ]
+    [license
+        Distributed under the Boost Software License, Version 1.0.
+        (See accompanying file LICENSE_1_0.txt or copy at
+        [@http://www.boost.org/LICENSE_1_0.txt])
+    ]
+]
+
+[/  Images   ]
+
+[def _note_                  [$images/note.png]]
+[def _alert_                 [$images/caution.png]]
+[def _detail_                [$images/note.png]]
+[def _tip_                   [$images/tip.png]]
+
+[/  Links   ]
+
+[def _sample_type_           '''<replaceable>sample-type</replaceable>''']
+[def _weight_type_           '''<replaceable>weight-type</replaceable>''']
+[def _variate_type_          '''<replaceable>variate-type</replaceable>''']
+[def _variate_tag_           '''<replaceable>variate-tag</replaceable>''']
+[def _left_or_right_         '''<replaceable>left-or-right</replaceable>''']
+[def _implementation_defined_ '''<replaceable>implementation-defined</replaceable>''']
+[def _boost_                 [@http://www.boost.org Boost]]
+[def _mpl_                   [@../../libs/mpl MPL]]
+[def _mpl_lambda_expression_ [@../../libs/mpl/doc/refmanual/lambda-expression.html MPL Lambda Expression]]
+[def _parameters_            [@../../libs/parameters Boost.Parameters]]
+[def _accumulator_set_       [classref boost::accumulators::accumulator_set `accumulator_set<>`]]
+[def _accumulator_base_      [classref boost::accumulators::accumulator_base `accumulator_base`]]
+[def _depends_on_            [classref boost::accumulators::depends_on `depends_on<>`]]
+[def _feature_of_            [classref boost::accumulators::feature_of `feature_of<>`]]
+[def _as_feature_            [classref boost::accumulators::as_feature `as_feature<>`]]
+[def _features_              [classref boost::accumulators::features `features<>`]]
+[def _external_              [classref boost::accumulators::external `external<>`]]
+[def _droppable_             [classref boost::accumulators::droppable `droppable<>`]]
+[def _droppable_accumulator_ [classref boost::accumulators::droppable_accumulator `droppable_accumulator<>`]]
+[def _extractor_             [classref boost::accumulators::tag::extractor `extractor<>`]]
+[def _tail_                  [classref boost::accumulators::tag::tail `tail`]]
+[def _tail_variate_          [classref boost::accumulators::tag::tail_variate `tail_variate<>`]]
+[def _extract_result_        [funcref boost::accumulators::extract_result `extract_result()`]]
+[def _ZKB_                   [@http://www.zkb.com Z'''&uuml;'''rcher Kantonalbank]]
+
+[section Preface]
+
+[:["It is better to be approximately right than exactly wrong.]\n['-- Old adage]]
+
+[h2 Description]
+
+Boost.Accumulators is both a library for incremental statistical computation as
+well as an extensible framework for incremental calculation in general. The library
+deals primarily with the concept of an ['accumulator], which is a primitive
+computational entity that accepts data one sample at a time and maintains some 
+internal state. These accumulators may offload some of their computations on other
+accumulators, on which they depend. Accumulators are grouped within an ['accumulator
+set]. Boost.Accumulators resolves the inter-dependencies between accumulators in a
+set and ensures that accumulators are processed in the proper order.
+
+[endsect]
+
+[section User's Guide]
+
+This section describes how to use the Boost.Accumulators framework to create new
+accumulators and how to use the existing statistical accumulators to perform incremental
+statistical computation. For detailed information regarding specific components in
+Boost.Accumulators, check the [link accumulators_framework_reference Reference] section.
+
+[h2 Hello, World!]
+
+Below is a complete example of how to use the Accumulators Framework and the 
+Statistical Accumulators to perform an incremental statistical calculation. It
+calculates the mean and 2nd moment of a sequence of doubles.
+
+    #include <iostream>
+    #include <boost/accumulators/accumulators.hpp>
+    #include <boost/accumulators/statistics/stats.hpp>
+    #include <boost/accumulators/statistics/mean.hpp>
+    #include <boost/accumulators/statistics/moment.hpp>
+    using namespace boost::accumulators;
+
+    int main()
+    {
+        // Define an accumulator set for calculating the mean and the
+        // 2nd moment ...
+        accumulator_set<double, stats<tag::mean, tag::moment<2> > > acc;
+
+        // push in some data ...
+        acc(1.2);
+        acc(2.3);
+        acc(3.4);
+        acc(4.5);
+
+        // Display the results ...
+        std::cout << "Mean:   " << mean(acc) << std::endl;
+        std::cout << "Moment: " << moment<2>(acc) << std::endl;
+
+        return 0;
+    }
+
+This program displays the following:
+
+[pre
+Mean:   2.85
+Moment: 9.635
+]
+
+[section The Accumulators Framework]
+
+The Accumulators Framework is framework for performing incremental calculations. Usage
+of the framework follows the following pattern:
+
+* Users build a computational object, called an ['_accumulator_set_], by selecting
+  the computations in which they are interested, or authoring their own computational
+  primitives which fit within the framework.
+* Users push data into the _accumulator_set_ object one sample at a time.
+* The _accumulator_set_ computes the requested quantities in the most efficient method
+  possible, resolving dependencies between requested calculations, possibly cacheing
+  intermediate results.
+
+The Accumulators Framework defines the utilities needed for defining primitive
+computational elements, called ['accumulators]. It also provides the _accumulator_set_
+type, described above.
+
+[h2 Terminology]
+
+The following terms are used in the rest of the documentation.
+
+[variablelist
+    [[Sample]          [[#sample_type] A datum that is pushed into an _accumulator_set_.
+                        The type of the sample is the ['sample type].]]
+    [[Weight]          [[#weight_type] An optional scalar value passed along with the
+                        sample specifying the weight of the sample. Conceptually, each
+                        sample is multiplied with its weight. The type of the weight is
+                        the ['weight type].]]
+    [[Feature]         [An abstract primitive computational entity. When defining an
+                        _accumulator_set_, users specify the features in which they are
+                        interested, and the _accumulator_set_ figures out which
+                        ['accumulators] would best provide those features. Features may
+                        depend on other features. If they do, the accumulator set figures
+                        out which accumulators to add to satisfy the dependencies.]]
+    [[Accumulator]     [A concrete primitive computational entity. An accumulator is a
+                        concrete implementation of a feature. It satisfies exactly one
+                        abstract feature. Several different accumulators may provide the
+                        same feature, but may represent different implementation strategies.]]
+    [[Accumulator Set] [A collection of accumulators. An accumulator set is specified with
+                        a sample type and a list of features. The accumulator set uses this
+                        information to generate an ordered set of accumulators depending on
+                        the feature dependency graph. An accumulator set accepts samples one
+                        datum at a time, propogating them to each accumulator in order. At any
+                        point, results can be extracted from the accumulator set.]]
+    [[Extractor]       [A function or function object that can be used to extract a result
+                        from an _accumulator_set_.]]
+]
+
+[h2 Overview]
+
+Here is a list of the important types and functions in the Accumulator Framework and
+a brief description of each.
+
+[table Accumulators Toolbox
+    [[Tool]              [Description]]
+    [[_accumulator_set_] [This is the most important type in the Accumulators Framework.
+                          It is a collection of accumulators. A datum pushed into an 
+                          _accumulator_set_ is forwarded to each accumulator, in an order
+                          determined by the dependency relationships between the
+                          accumulators. Computational results can be extracted from an
+                          accumulator at any time.]]
+    [[_depends_on_     ] [Used to specify which other features a feature depends on.]]
+    [[_feature_of_     ] [Trait used to tell the Accumulators Framework that, for the purpose
+                          of feature-based dependency resolution, one feature should be
+                          treated the same as another.]]
+    [[_as_feature_     ] [Used to create an alias for a feature. For example, if there are
+                          two features, fast_X and accurate_X, they can be mapped to
+                          X(fast) and X(accurate) with _as_feature_. This is just syntactic
+                          sugar.]]
+    [[_features_       ] [An _mpl_ sequence. We can use _features_ as the second template
+                          parameter when declaring an _accumulator_set_.]]
+    [[_external_       ] [Used when declaring an _accumulator_set_. If the weight type is
+                          specified with _external_, then the weight accumulators are
+                          assumed to reside in a separate accumulator set which will be passed
+                          in with a named parameter.]]
+    [[_extractor_      ] [A class template useful for creating an extractor function object.
+                          It is parameterized on a feature, and it has member functions for
+                          extracting from an _accumulator_set_ the result corresponding to
+                          that feature.]]
+]
+
+[section Using [^accumulator_set<>]]
+
+Our tour of the _accumulator_set_ class template begins with the forward declaration:
+
+    template< typename Sample, typename Features, typename Weight = void >
+    struct accumulator_set;
+
+The template parameters have the following meaning:
+
+[variablelist
+    [[`Sample`]     [The type of the data that will be accumulated.]]
+    [[`Features`]   [An _mpl_ sequence of features to be calculated.]]
+    [[`Weight`]     [The type of the (optional) weight paramter.]]
+]
+
+For example, the following line declares an _accumulator_set_ that will accept
+a sequence of doubles one at a time and calculate the min and mean:
+
+    accumulator_set< double, features< tag::min, tag::mean > > acc;
+
+Notice that we use the _features_ template to specify a list of features to be calculated.
+_features_ is an MPL sequence of features.
+
+[note _features_ is a synonym of `mpl::vector<>`. In fact, we could use `mpl::vector<>`
+ or any MPL sequence if we prefer, and the meaning would be the same.]
+
+Once we have defined an _accumulator_set_, we can then push data into it,
+and it will calculate the quantities you requested, as shown below.
+
+    // push some data into the accumulator_set ...
+    acc(1.2);
+    acc(2.3);
+    acc(3.4);
+
+Since _accumulator_set_ defines its accumulate function to be the function call operator,
+we might be tempted to use an _accumulator_set_ as a UnaryFunction to a standard
+algorithm such as `std::for_each`. That's fine as long as we keep in mind that the standard
+algorithms take UnaryFunction objects by value, which involves making a copy of the
+_accumulator_set_ object. Consider the following:
+
+    // The data for which we wish to calculate statistical properties:
+    std::vector< double > data( /* stuff */ );
+
+    // The accumulator set which will calculate the properties for us:    
+    accumulator_set< double, features< tag::min, tag::mean > > acc;
+
+    // Use std::for_each to accumulate the statistical properties:
+    acc = std::for_each( data.begin(), data.end(), acc );
+
+Notice how we must assign the return value of `std::for_each` back to the _accumulator_set_.
+This works, but some accumulators are not cheap to copy. For
+example, the _tail_ and _tail_variate_ accumulators must store a `std::vector<>`, so copying
+these accumulators involves a dynamic allocation. We might be better off in this
+case to define a wrapper that stores a reference to an _accumulator_set_ and forwards the
+function call operator to it. See below:
+
+    template< typename Sample, typename Features, typename Weight >
+    struct accumulator_set_wrapper
+      : std::unary_function< Sample, void >
+    {
+        accumulator_set_wrapper( accumulator_set< Sample, Features, Weight > & acc )
+          : acc_(acc)
+        {
+        }
+        
+        void operator()( Sample const & sample )
+        {
+            this->acc_( sample );
+        }
+    private:
+        accumulator_set< Sample, Features, Weight > & acc_;
+    };
+
+    template< typename Sample, typename Features, typename Weight >
+    accumulator_set_wrapper< typename Sample, typename Features, typename Weight >
+    make_accumulator_set_wrapper( accumulator_set< Sample, Features, Weight > & acc )
+    {
+        return acc;
+    }
+
+You might use such an `accumulator_set_wrapper<>` as follows:
+
+    // The data for which we wish to calculate statistical properties:
+    std::vector< double > data( /* stuff */ );
+
+    // The accumulator set which will calculate the properties for us:
+    accumulator_set< double, features< tag::tail<left> > > acc( 
+        tag::tail<left>::cache_size = 4 );
+
+    // Use std::for_each to accumulate the statistical properties:
+    std::for_each( data.begin(), data.end(), make_accumulator_set_wrapper( acc ) );
+
+Notice now that we don't care about the return value of `std::for_each` anymore because
+`std::for_each` is modifying `acc` directly.
+
+[endsect]
+
+[section Extracting Results]
+
+Once we have declared an _accumulator_set_ and pushed data into it, we need to be able
+to extract results from it. For each feature we can add to an _accumulator_set_, there
+is a corresponding extractor for fetching its result. Usually, the extractor has the
+same name as the feature, but in a different namespace. For example, if we accumulate
+the `tag::min` and `tag::max` features, we can extract the results with the `min` and `max`
+extractors, as follows:
+
+    // Calculate the minimum and maximum for a sequence of integers.
+    accumulator_set< int, features< tag::min, tag::max > > acc;
+    acc( 2 );
+    acc( -1 );
+    acc( 1 );
+
+    // This displays "(-1, 2)"
+    std::cout << '(' << min( acc ) << ", " << max( acc ) << ")\n";
+
+The extractors are all declared in the `boost::accumulators::extract` namespace, but they
+are brought into the `boost::accumulators` namespace with a `using` declaration.
+
+[tip On the Windows platform, `min` and `max` are preprocessor macros defined in [^WinDef.h].
+ To use the `min` and `max` extractors, you should either compile with `NOMINMAX` defined, or
+ you should invoke the extractors like: `(min)( acc )` and `(max)( acc )`. The parentheses
+ keep the macro from being invoked.]
+
+Another way to extract a result from an _accumulator_set_ is with the
+`extract_result()` function. This can be more convenient if there isn't an extractor
+object handy for a certain feature. The line above which displays results could 
+equally be written as:
+
+    // This displays "(-1, 2)"
+    std::cout << '('  << extract_result< tag::min >( acc )
+              << ", " << extract_result< tag::max >( acc ) << ")\n";
+
+Finally, we can define our own extractor using the _extractor_ class template. For
+instance, another way to avoid the `min` / `max` macro business would be to define 
+extractors with names that don't conflict with the macros, like this:
+
+    extractor< tag::min > min_;
+    extractor< tag::min > max_;
+
+    // This displays "(-1, 2)"
+    std::cout << '(' << min_( acc ) << ", " << max_( acc ) << ")\n";
+
+[endsect]
+
+[section Passing Optional Parameters]
+
+Some accumulators need initialization parameters. In addition, perhaps some auxiliary
+information needs to be passed into the _accumulator_set_ along with each sample.
+Boost.Accumulators handles these cases with named parameters from the _parameters_
+library.
+
+For example, consider the _tail_ and _tail_variate_ features. _tail_ keeps
+an ordered list of the largest [^['N]] samples, where [^['N]] can be specified at
+construction time. Also, the _tail_variate_ feature, which depends on _tail_, keeps
+track of some data that is covariate with the [^['N]] samples tracked by _tail_. The
+code below shows how this all works, and is described in more detail below.
+
+    // Define a feature for tracking covariate data
+    typedef tag::tail_variate< int, tag::covariate1, left > my_tail_variate_tag;
+
+    // This will calculate the left tail and my_order_variate for N == 2
+    // using the tag::tail<left>::cache_size named parameter
+    accumulator_set< double, features< my_tail_variate_tag > > acc( 
+        tag::tail<left>::cache_size = 2 );
+
+    // push in some samples and some covariates by using 
+    // the covariate1 named parameter
+    acc( 1.2, covariate1 =  12 );
+    acc( 2.3, covariate1 = -23 );
+    acc( 3.4, covariate1 =  34 );
+    acc( 4.5, covariate1 = -45 );
+
+    // Define an extractor for the my_tail_variate_tag feature
+    extractor< my_tail_variate_tag > my_order_variate;
+    
+    // Write the tail statistic to std::cout. This will print "4.5, 3.4, "
+    std::ostream_iterator< double > dout( std::cout, ", " );
+    std::copy( tail( acc ).begin(), tail( acc ).end(), dout );
+    
+    // Write the tail_variate statistic to std::cout. This will print "-45, 34, "
+    std::ostream_iterator< int > iout( std::cout, ", " );
+    std::copy( my_order_variate( acc ).begin(), my_order_variate( acc ).end(), iout );
+
+There are several things to note about the code above. First, notice that we didn't have
+to request that the _tail_ feature be calculated. That is implicit because the _tail_variate_
+feature depends on the _tail_ feature. Next, notice how the `acc` object
+is initialized: `acc( tag::tail<left>::cache_size = 2 )`. Here, `cache_size` is a named parameter.
+It is used to tell the _tail_ and _tail_variate_ accumulators how many samples and
+covariates to store. Conceptually, every construction parameter is made available to
+every accumulator in an accumulator set. 
+
+We also use a named parameter to pass covariate data into the accumulator set along with
+the samples. As with the constructor parameters, all parameters to the accumulate function
+are made available to all the accumulators in the set. In this case, only the accumulator
+for the `my_order_variate` feature would be interested in the value of the `covariate1` named
+parameter.
+
+We can make one final observation about the example above. Since _tail_ and _tail_variate_
+are multi-valued features, the result we extract for them is represented as an iterator
+range. That is why we can say `tail( acc ).begin()` and `tail( acc ).end()`.
+
+Even the extractors can accept named parameters. In a bit, we'll see a situation where that
+is useful.
+
+[endsect]
+
+[section Weighted Samples]
+
+Some accumulators, statistical accumulators in particular, deal with data that are
+['weighted]. Each sample pushed into the accumulator has an associated weight, by which
+the sample is conceptually multiplied. The Statistical Accumulators Library provides an 
+assortment of these weighted statistical accumulators. And many unweighted statistical
+accumulators have weighted variants. For instance, the weighted variant of the `sum`
+accumulator is called `weighted_sum`, and is calculated by accumulating all the
+samples multiplied by their weights.
+
+To declare an _accumulator_set_ that accepts weighted samples, you must specify the
+type of the weight parameter as the 3rd template parameter, as follows:
+
+    // 3rd template parameter 'int' means this is a weighted
+    // accumulator set where the weights have type 'int'
+    accumulator_set< int, features< tag::sum >, int > acc;
+
+When you specify a weight, all the accumulators in the set are replaced with
+their weighted equivalents. For example, the above _accumulator_set_ declaration
+is equivalent to the following:
+
+    // Since we specified a weight, tag::sum becomes tag::weighted_sum
+    accumulator_set< int, features< tag::weighted_sum >, int > acc;
+
+When passing samples to the accumulator set, you must also specify the 
+weight of each sample. You can do that with the `weight` named parameter,
+as follows:
+
+    acc(1, weight = 2); //   1 * 2
+    acc(2, weight = 4); //   2 * 4
+    acc(3, weight = 6); // + 3 * 6
+                        // -------
+                        // =    28
+
+You can then extract the result with the `sum()` extractor, as follows:
+
+    // This prints "28"
+    std::cout << sum(acc) << std::endl;
+
+[note When working with weighted statistical accumulators from the Statistical
+Accumulators Library, be sure to include the appropriate header. For instance, 
+`weighted_sum` is defined in `<boost/accumulators/statistics/weighted_sum.hpp>`.]
+
+[endsect]
+
+[section Numeric Operators Sub-Library]
+
+This section describes the function objects in the `boost::numeric` namespace, which
+is a sub-library that provides function objects and meta-functions corresponding
+to the infix operators in C++.
+
+In the `boost::numeric::operators` namespace are additional operator overloads for
+some useful operations not provided by the standard library, such as multiplication 
+of a `std::complex<>` with a scalar.
+
+In the `boost::numeric::functional` namespace are function object equivalents of 
+the infix operators. These function object types are heterogeneous, and so are more 
+general than the standard ones found in the [^<functional>] header. They use the
+Boost.Typeof library to deduce the return types of the infix expressions they
+evaluate. In addition, they look within the `boost::numeric::operators` namespace
+to consider any additional overloads that might be defined there.
+
+In the `boost::numeric` namespace are global polymorphic function objects 
+corresponding to the function object types defined in the `boost::numeric::functional`
+namespace. For example, `boost::numeric::plus(a, b)` is equivalent to
+`boost::numeric::functional::plus<A, B>()(a, b)`, and both are equivalent to
+`using namespace boost::numeric::operators; a + b;`.
+
+The Numeric Operators Sub-Library also gives several ways to sub-class and
+a way to sub-class and specialize operations. One way uses tag dispatching on
+the types of the operands. The other way is based on the compile-time
+properties of the operands.
+
+[endsect]
+
+[section Extending the Accumulators Framework]
+
+This section describes how to extend the Accumulators Framework by defining new accumulators,
+features and extractors. Also covered are how to control the dependency resolution of
+features within an accumulator set.
+
+[section Defining a New Accumulator]
+
+All new accumulators must satisfy the [link
+accumulators.user_s_guide.the_accumulators_framework.concepts.accumulator_concept Accumulator
+Concept]. Below is a sample class that satisfies the accumulator concept, which simply sums
+the values of all samples passed into it.
+
+    #include <boost/accumulators/framework/accumulator_base.hpp>
+    #include <boost/accumulators/framework/parameters/sample.hpp>
+    
+    namespace boost {                           // Putting your accumulators in the
+    namespace accumulators {                    // impl namespace has some
+    namespace impl {                            // advantages. See below.
+    
+    template<typename Sample>
+    struct sum_accumulator                      // All accumulators should inherit from
+      : accumulator_base                        // accumulator_base.
+    {
+        typedef Sample result_type;             // The type returned by result() below.
+        
+        template<typename Args>                 // The constructor takes an argument pack.
+        sum_accumulator(Args const & args)
+          : sum(args[sample | Sample()])        // Maybe there is an initial value in the
+        {                                       // argument pack. ('sample' is defined in
+        }                                       // sample.hpp, included above.)
+        
+        template<typename Args>                 // The accumulate function is the function
+        void operator ()(Args const & args)     // call operator, and it also accepts an
+        {                                       // argument pack.
+            this->sum += args[sample];
+        }
+        
+        result_type result(dont_care) const     // The result function will also be passed
+        {                                       // an argument pack, but we don't use it here,
+            return this->sum;                   // so we use "dont_care" as the argument type.
+        }
+    private:
+        Sample sum;
+    };
+    
+    }}}
+
+Much of the above should be pretty self-explanitory, except for the use of argument packs
+which may be confusing if you have never used the _parameters_ library before. An argument
+pack is a cluster of values, each of which can be accessed with a key. So `args[sample]`
+extracts from the pack the value associated with the `sample` key. And the cryptic
+`args[sample | Sample()]` evaluates to the value associated with the `sample` key if it
+exists, or a default-constructed `Sample` if it doesn't.
+
+The example above demonstrates the most common attributes of an accumulator. There are
+other optional member functions that have special meaning. In particular:
+
+[variablelist Optional Accumulator Member Functions
+[[[^on_drop(Args)]]         [Defines an action to be taken when this accumulator is
+                             dropped. See the section on
+                             [link accumulators.user_s_guide.the_accumulators_framework.extending_the_accumulators_framework.defining_a_new_accumulator.droppable_accumulators
+                              Droppable Accumulators].]]
+[[[^post_construct(Args)]]  [An action to be executed after all accumulators in the
+                             accumulator set have been constructed. This is useful when the
+                             successful initialization of one accumulator depends on another
+                             accumulator.]]
+]
+
+[h3 Accessing Other Accumulators in the Set]
+
+Some accumulators depend on other accumulators within the same accumulator set. In those
+cases, it is necessary to be able to access those other accumulators. To make this possible,
+the _accumulator_set_ passes a reference to itself when invoking the member functions of
+its contained accumulators. It can be accessed by using the special `accumulator` key with
+the argument pack. Consider how we might implement `mean_accumulator`:
+
+    // Mean == (Sum / Count)
+    template<typename Sample>
+    struct mean_accumulator : accumulator_base
+    {
+        typedef Sample result_type;
+        mean_accumulator(dont_care) {}
+
+        template<typename Args>
+        result_type result(Args const &args) const
+        {
+            return sum(args[accumulator]) / count(args[accumulator]);
+        }
+    };
+
+`mean` depends on the `sum` and `count` accumulators. (We'll see in the next section how
+to specify these dependencies.) The result of the mean accumulator is merely the result of 
+the sum accumulator divided by the result of the count accumulator. Consider how we write
+that: `sum(args[accumulator]) / count(args[accumulator])`. The expression `args[accumulator]`
+evaluates to a reference to the _accumulator_set_ that contains this `mean_accumulator`. It
+also contains the `sum` and `count` accumulators, and we can access their results with the
+extractors defined for those features: `sum` and `count`.
+
+[note Accumulators that inherit from _accumulator_base_ get an empty `operator ()`, so
+ accumulators like `mean_accumulator` above need not define one.]
+
+All the member functions that accept an argument pack have access to the enclosing 
+_accumulator_set_ via the `accumulator` key, with one exception: the constructor. The
+order in which accumulators within the set are constructed is unspecified. As a result,
+it would not be safe for one accumulator to access another during construction. If there are
+initialization dependencies between accumulators in the set, those can be managed with
+`post_construct(Args)`. The _accumulator_set_ post-constructs all its contained accumulators,
+in an order that satisfies the dependency relationships between them.
+
+[h3 Infix Notation and the Numeric Operators Sub-Library]
+
+Although not necessary, it can be a good idea to put your accumulator implementations in 
+the `boost::accumulators::impl` namespace. This namespace pulls in any operators defined
+in the `boost::numeric::operators` namespace with a using directive. The Numeric Operators 
+Sub-Library defines some additional overloads that will make your accumulators work with 
+all sorts of data types.
+
+Consider `mean_accumulator` defined above. It divides the sum of the samples by the count.
+The type of the count is `std::size_t`. What if the sample type doesn't define division by
+`std::size_t`? That's the case for `std::complex<>`. You might think that if the sample type
+is `std::complex<>`, the code would not work, but in fact it does. That's because
+Numeric Operators Sub-Library defines an overloaded `operator/` for `std::complex<>` 
+and `std::size_t`. This operator is defined in the `boost::numeric::operators` namespace and
+will be found within the `boost::accumulators::impl` namespace. That's why it's a good idea
+to put your accumulators there.
+
+[h3 Droppable Accumulators]
+
+The term "droppable" refers to an accumulator that can be removed from the _accumulator_set_.
+You can request that an accumulator be made droppable by using the _droppable_ class template,
+as follows:
+
+    // calculate sum and mean, make mean droppable
+    accumulator_set< double, features< tag::sum, droppable<tag::mean> > > acc;
+    
+    // add some data
+    acc(1.0);
+    acc(2.0);
+
+    // drop the mean (mean is 1.5 here)
+    acc.drop<tag::mean>();
+    
+    // add more data
+    acc(3.0);
+    
+    // This will display "3" and "1.5"
+    std::cout << sum(acc) << '\n' << mean(acc);    
+
+Dropping an accumulator essentially freezes it in its current state. It no longer gets
+updates. For many accumulators, not receiving updates is sufficient to freeze their
+states. But for the `mean_accumulator` defined above, that's not the case. Its
+result depends on the `sum` and `count` accumulators, which are not frozen. Instead,
+it needs to save its result at the point it is dropped. The Accumulators Framework
+provides some utilities to make this simple. Simply create the following
+specialization of _droppable_accumulator_:
+
+    namespace boost { namespace accumulators {
+    
+    // cache the result at the point the accumulator is dropped.
+    template<typename Sample>
+    struct droppable_accumulator<impl::mean_accumulator<Sample> >
+      : droppable_accumulator_base<
+            with_cached_result<impl::mean_accumulator<Sample> >
+        >
+    {
+        template<typename Args>
+        droppable_accumulator(Args const & args)
+          : droppable_accumulator_base<
+                with_cached_result<impl::mean_accumulator<Sample> >
+            >(args)
+        {
+        }
+    };
+    
+    }}
+
+This specialization will get used whenever `mean_accumulator<>` is made droppable.
+The `with_cached_result<>` utility causes the result to be cached at the point
+the accumulator is dropped by implementing `on_drop(Args)` appropriately.
+
+[endsect]
+
+[section Defining a New Feature]
+
+Once we have implemented an accumulator, we must define a feature for it so
+that users can specify the feature when declaring an _accumulator_set_. We
+typically put the features into a nested namespace, so that later we can
+define an extractor of the same name. All features must satisfy the
+[link accumulators.user_s_guide.the_accumulators_framework.concepts.feature_concept
+Feature Concept]. Using _depends_on_ makes satisfying the concept simple.
+Below is an example of a feature definition.
+
+    namespace boost { namespace accumulators { namespace tag {
+    
+    struct mean                         // Features should inherit from
+      : depends_on< count, sum >        // depends_on<> to specify dependencies
+    {
+        // Define a nested typedef called 'impl' that specifies which
+        // accumulator implements this feature. 
+        typedef impl::mean_accumulator< mpl::_1 > impl;
+    };
+    
+    }}}
+
+The only two things we must do to define the `mean` feature is to specify the
+dependencies with _depends_on_ and define the nested `impl` typedef. Even features
+that have no dependencies should inherit from _depends_on_. The nested `impl` type
+must be an _mpl_lambda_expression_. The result of 
+`mpl::apply< impl, _sample_type_, _weight_type_ >::type` must be
+be the type of the accumulator that implements this feature. The use of _mpl_
+placeholders like `mpl::_1` make it especially easy to make a template such
+as `mean_accumulator<>` an _mpl_lambda_expression_. Here, `mpl::_1` will be
+replaced with the sample type. Had we used `mpl::_2`, it would have been replaced
+with the weight type.
+
+What about accumulator types that are not templates? If you have a `foo_accumulator`
+which is a plain struct and not a template, you could turn it into an
+_mpl_lambda_expression_ using `mpl::always<>`, like this:
+
+    // An MPL lambda expression that always evaluates to
+    // foo_accumulator:
+    typedef mpl::always< foo_accumulator > impl;
+
+If you are ever unsure, or if you are not comfortable with MPL lambda expressions,
+you could always define `impl` explicitly:
+
+    // Same as 'typedef mpl::always< foo_accumulator > impl;'
+    struct impl
+    {
+        template< typename Sample, typename Weight >
+        struct apply
+        {
+            typedef foo_accumulator type;
+        };
+    };
+
+Here, `impl` is a binary [@../../libs/mpl/doc/refmanual/metafunction-class.html
+MPL Metafunction Class], which is a kind of _mpl_lambda_expression_. The nested
+`apply<>` template is part of the metafunction class protocol and tells MPL how
+to to build the accumulator type given the sample and weight types.
+
+All features must also provide a nested `is_weight_accumulator` typedef. It must
+be either `mpl::true_` or `mpl::false_`. _depends_on_ provides a default of 
+`mpl::false_` for all features that inherit from it, but that can be overridden
+(or hidden, technically speaking) in the derived type. When the feature represents
+an accumulation of information about the weights instead of the samples, we
+can mark this feature as such with `typedef mpl::true_ is_weight_accumulator;`.
+The weight accumulators are made external if the weight type is specified using
+the _external_ template.
+
+[endsect]
+
+[section Defining a New Extractor]
+
+Now that we have an accumulator and a feature, the only thing lacking is a way
+to get results from the accumulator set. The Accumulators Framework provides the
+_extractor_ class template to make it simple to define an extractor for your
+feature. Here's an extractor for the `mean` feature we defined above:
+
+    namespace boost {
+    namespace accumulators {                // By convention, we put extractors
+    namespace extract {                     // in the 'extract' namespace
+    
+    extractor< tag::mean > const mean = {}; // Simply define our extractor with
+                                            // our feature tag, like this.
+    }
+    using extract::mean;                    // Pull the extractor into the
+                                            // enclosing namespace.
+    }}                                            
+
+Once defined, the `mean` extractor can be used to extract the result of the
+`tag::mean` feature from an _accumulator_set_.
+
+Parameterized features complicate this simple picture. Consider the `moment`
+feature, for calculating the [^['N]]-th moment, where [^['N]] is specified as
+a template parameter:
+
+    // An accumulator set for calculating the N-th moment, for N == 2 ...
+    accumulator_set< double, features< tag::moment<2> > > acc;
+    
+    // ... add some data ...
+    
+    // Display the 2nd moment ...
+    std::cout << "2nd moment is " << moment<2>(acc) << std::endl;
+
+In the expression `moment<2>(acc)`, what is `moment`? It cannot be an object --
+the syntax of C++ will not allow it. Clearly, if we want to provide this syntax,
+we must make `moment` a function template. Here's what the definition of the 
+`moment` extractor looks like:
+
+    namespace boost {
+    namespace accumulators {                // By convention, we put extractors
+    namespace extract {                     // in the 'extract' namespace
+    
+    template<int N, typename AccumulatorSet>
+    typename mpl::apply<AccumulatorSet, tag::moment<N> >::type::result_type
+    moment(AccumulatorSet const &acc)
+    {
+        return extract_result<tag::moment<N> >(acc);
+    }
+    
+    }
+    using extract::moment;                  // Pull the extractor into the
+                                            // enclosing namespace.
+    }}                                            
+
+The return type deserves some explanation. Every _accumulator_set_ type
+is actually a unary [@../../libs/mpl/doc/refmanual/metafunction-class.html
+MPL Metafunction Class]. When you `mpl::apply<>` an _accumulator_set_ and
+a feature, the result is the type of the accumulator within the set that
+implements that feature. And every accumulator provides a nested `result_type`
+typedef that tells what its return type is. The extractor simply delegates
+its work to the _extract_result_ function.
+
+[endsect]
+
+[section Controlling Dependencies]
+
+The feature-based dependency resolution of the Accumulators Framework is
+designed to allow multiple different implementation strategies for each
+feature. For instance, two different accumulators may calculate the same
+quantity with different rounding modes, or using different algorithms with
+different size/speed tradeoffs. Other accumulators that depend on that
+quantity shouldn't care how it's calculated. The Accumulators Framework
+handles this by allowing several different accumulators satisfy the same
+feature.
+
+
+* Mapping multiple impls to the same feature with feature_of
+* Creating aliases for features with as_feature
+
+[endsect]
+
+[section:operators_ex Adding or Specializing Operator (Meta-) Functions]
+
+TODO
+
+[endsect]
+
+[endsect]
+
+[section Concepts]
+
+[h2 Accumulator Concept]
+
+In the following table, `Acc` is the type of an accumulator, `acc` and `acc2` are objects of type
+`Acc`, and `args` is the name of an argument pack from the _parameters_ library.
+
+[table Accumulator Requirements
+    [[[*Expression]]                 [[*Return type]]       [[*Assertion / Note /
+                                                               Pre- / Post-condition]]]
+    [[`Acc::result_type`]            [['implementation
+                                       defined]]            [The type returned by `Acc::result()`.]]
+    [[`Acc acc(args)`]               [none]                 [Construct from an argument pack.]]
+    [[`Acc acc(acc2)`]               [none]                 [Pre: `acc2` has been post-constructed.
+                                                             Post: `acc.result(args)` is equivalent
+                                                             to `acc2.result(args)`]]
+    [[`acc(args)`]                   [['unspecified]]       [Pre: `acc` has been post-constructed.]]
+    [[`acc.post_construct(args)`]    [['unspecified]]       [Run `acc`'s post-constructor.]]
+    [[`acc.on_drop(args)`]           [['unspecified]]       [Pre: `acc` has been post-constructed.]]
+    [[`acc.result(args)`]            [`Acc::result_type`]   [Pre: `acc` has been post-constructed.]]
+]
+
+[h2 Feature Concept]
+
+In the following table, `F` is the type of a feature and `S` is some scalar type.
+
+[table Featue Requirements
+    [[[*Expression]]                 [[*Return type]]       [[*Assertion / Note /
+                                                               Pre- / Post-condition]]]
+    [[`F::dependencies`]             [['unspecified]]       [An MPL sequence of other features on
+                                                             which which `F` depends.]]
+    [[`F::is_weight_accumulator`]    [`mpl::true_` or
+                                      `mpl::false_`]        [`mpl::true_` if the accumulator for
+                                                             this feature should be made external
+                                                             when the weight type for the accumulator
+                                                             set is `external<S>`, `mpl::false_`
+                                                             otherwise.]]
+    [[`F::impl`]                     [['unspecified]]       [An _mpl_lambda_expression_ that
+                                                             returns the type of the accumulator that
+                                                             implements this feature when passed a
+                                                             sample type and a weight type.]]
+]
+
+[endsect]
+
+[endsect]
+
+[section The Statistical Accumulators Library]
+
+The Statistical Accumulators Library defines accumulators for incremental statistial
+computations. It is built on top of [link accumulators.user_s_guide.the_accumulators_framework
+The Accumulator Framework].
+
+[section:count count]
+
+The `count` feature is a simple counter that tracks the
+number of samples pushed into the accumulator set.
+
+[variablelist
+    [[Result Type] [``
+                    std::size_t
+                    ``]]
+    [[Depends On] [['none]]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<int, features<tag::count> > acc;
+    acc(0);
+    acc(0);
+    acc(0);
+    assert(3 == count(acc));
+
+[*See also]
+
+* [classref boost::accumulators::impl::count_impl `count_impl`]
+
+[endsect]
+
+[section:covariance covariance]
+
+The `covariance` feature is an iterative Monte Carlo estimator for the covariance.
+It is specified as `tag::covariance<_variate_type_, _variate_tag_>`.
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::outer_product<
+                        numeric::functional::average<_sample_type_, std::size_t>::result_type
+                      , numeric::functional::average<_variate_type_, std::size_t>::result_type
+                    >::result_type
+                    ``]]
+    [[Depends On] [`count` \n `mean` \n `mean_of_variates<_variate_type_, _variate_tag_>`]]
+    [[Variants] [`abstract_covariance`]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [[~variate-tag]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<double, stats<tag::covariance<double, tag::covariate1> > > acc;
+    acc(1., covariate1 = 2.);
+    acc(1., covariate1 = 4.);
+    acc(2., covariate1 = 3.);
+    acc(6., covariate1 = 1.);
+    assert(covariance(acc) == -1.75);
+
+[*See also]
+
+* [classref boost::accumulators::impl::covariance_impl [^covariance_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.mean [^mean]]
+
+[endsect]
+
+[section:density density]
+
+The `tag::density` feature returns a histogram of the sample distribution. For more
+implementation details, see [classref boost::accumulators::impl::density_impl [^density_impl]].
+
+[variablelist
+    [[Result Type] [``
+                    iterator_range<
+                        std::vector<
+                            std::pair<
+                                numeric::functional::average<_sample_type_, std::size_t>::result_type
+                              , numeric::functional::average<_sample_type_, std::size_t>::result_type
+                            >
+                        >::iterator
+                    >
+                    ``]]
+    [[Depends On] [`count` \n `min` \n `max`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [`density::cache_size` \n `density::num_bins`]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [O(N), when N is `density::num_bins`]] 
+]
+
+[/ TODO add example ]
+
+[*See also]
+
+* [classref boost::accumulators::impl::density_impl [^density_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.min [^min]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.max [^max]]
+
+[endsect]
+
+[section:error_of_mean error_of<mean>]
+
+The `error_of<mean>` feature calculates the error of the mean feature. It is equal to
+`sqrt(variance / (count - 1))`.
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, std::size_t>::result_type
+                    ``]]
+    [[Depends On] [`count` \n `variance`]]
+    [[Variants] [`error_of<immediate_mean>`]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<double, stats<tag::error_of<tag::mean> > > acc;
+    acc(1.1);
+    acc(1.2);
+    acc(1.3);
+    assert(0.057735 == error_of<tag::mean>(acc));
+
+[*See also]
+
+* [classref boost::accumulators::impl::error_of_mean_impl [^error_of_mean_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.variance [^variance]]
+
+[endsect]
+
+[section:extended_p_square extended_p_square]
+
+Multiple quantile estimation with the extended [^P^2] algorithm. For further 
+details, see [classref boost::accumulators::impl::extended_p_square_impl [^extended_p_square_impl]].
+
+[variablelist
+    [[Result Type] [``
+                    boost::iterator_range<
+                        _implementation_defined_
+                    >
+                    ``]]
+    [[Depends On] [`count`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [`tag::extended_p_square::probabilities`]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    boost::array<double> probs = {0.001,0.01,0.1,0.25,0.5,0.75,0.9,0.99,0.999};
+    accumulator_set<double, stats<tag::extended_p_square> >
+        acc(tag::extended_p_square::probabilities = probs);
+
+    boost::lagged_fibonacci607 rng; // a random number generator
+    for (int i=0; i<10000; ++i)
+        acc(rng());
+
+    BOOST_CHECK_CLOSE(extended_p_square(acc)[0], probs[0], 25);
+    BOOST_CHECK_CLOSE(extended_p_square(acc)[1], probs[1], 10);
+    BOOST_CHECK_CLOSE(extended_p_square(acc)[2], probs[2], 5);
+    
+    for (std::size_t i=3; i < probs.size(); ++i)
+    {
+        BOOST_CHECK_CLOSE(extended_p_square(acc)[i], probs[i], 2);
+    }
+
+[*See also]
+
+* [classref boost::accumulators::impl::extended_p_square_impl [^extended_p_square_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+
+[endsect]
+
+[section:extended_p_square_quantile extended_p_square_quantile ['and variants]]
+
+Quantile estimation using the extended [^P^2] algorithm for weighted and unweighted samples.
+By default, the calculation is linear and unweighted, but quadratic and weighted variants 
+are also provided. For further implementation details, see 
+[classref boost::accumulators::impl::extended_p_square_quantile_impl [^extended_p_square_quantile_impl]].
+
+All the variants share the `tag::quantile` feature and can be extracted using the `quantile()`
+extractor.
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, std::size_t>::result_type
+                    ``]]
+    [[Depends On] [weighted variants depend on `weighted_extended_p_square` \n
+                   unweighted variants depend on `extended_p_square`]]
+    [[Variants] [`extended_p_square_quantile_quadratic` \n 
+                 `weighted_extended_p_square_quantile` \n 
+                 `weighted_extended_p_square_quantile_quadratic`]]
+    [[Initialization Parameters] [`tag::extended_p_square::probabilities`]]
+    [[Accumulator Parameters] [`weight` for the weighted variants]]
+    [[Extractor Parameters] [`quantile_probability`]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [O(N) where N is the count of probabilities.]] 
+]
+
+[*Example]
+
+    typedef accumulator_set<double, stats<tag::extended_p_square_quantile> >
+        accumulator_t;
+    typedef accumulator_set<double, stats<tag::weighted_extended_p_square_quantile>, double >
+        accumulator_t_weighted;
+    typedef accumulator_set<double, stats<tag::extended_p_square_quantile(quadratic)> >
+        accumulator_t_quadratic;
+    typedef accumulator_set<double, stats<tag::weighted_extended_p_square_quantile(quadratic)>, double >
+        accumulator_t_weighted_quadratic;
+
+    // tolerance
+    double epsilon = 1;
+
+    // a random number generator
+    boost::lagged_fibonacci607 rng;
+
+    boost::array<double> probs = { 0.990, 0.991, 0.992, 0.993, 0.994, 
+                                   0.995, 0.996, 0.997, 0.998, 0.999 };
+    accumulator_t acc(extended_p_square_probabilities = probs);
+    accumulator_t_weighted acc_weighted(extended_p_square_probabilities = probs);
+    accumulator_t_quadratic acc2(extended_p_square_probabilities = probs);
+    accumulator_t_weighted_quadratic acc_weighted2(extended_p_square_probabilities = probs);
+    
+    for (int i=0; i<10000; ++i)
+    {
+        double sample = rng();
+        acc(sample);
+        acc2(sample);
+        acc_weighted(sample, weight = 1.);
+        acc_weighted2(sample, weight = 1.);
+    }
+    
+    for (std::size_t i = 0; i < probs.size() - 1; ++i)
+    {
+        BOOST_CHECK_CLOSE(
+            quantile(acc, quantile_probability = 0.99025 + i*0.001)
+          , 0.99025 + i*0.001
+          , epsilon
+        );
+        BOOST_CHECK_CLOSE(
+            quantile(acc2, quantile_probability = 0.99025 + i*0.001)
+          , 0.99025 + i*0.001
+          , epsilon
+        );
+        BOOST_CHECK_CLOSE(
+            quantile(acc_weighted, quantile_probability = 0.99025 + i*0.001)
+          , 0.99025 + i*0.001
+          , epsilon
+        );
+        BOOST_CHECK_CLOSE(
+            quantile(acc_weighted2, quantile_probability = 0.99025 + i*0.001)
+          , 0.99025 + i*0.001
+          , epsilon
+        );
+    }
+
+[*See also]
+
+* [classref boost::accumulators::impl::extended_p_square_quantile_impl [^extended_p_square_quantile_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.extended_p_square [^extended_p_square]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.weighted_extended_p_square [^weighted_extended_p_square]]
+
+[endsect]
+
+[section:kurtosis kurtosis]
+
+The kurtosis of a sample distribution is defined as the ratio of the 4th central moment and the
+square of the 2nd central moment (the variance) of the samples, minus 3. The term [^-3] is added
+in order to ensure that the normal distribution has zero kurtosis. For more implementation 
+details, see [classref boost::accumulators::impl::kurtosis_impl [^kurtosis_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, _sample_type_>::result_type
+                    ``]]
+    [[Depends On] [`mean` \n `moment<2>` \n `moment<3>` \n `moment<4>`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<int, stats<tag::kurtosis > > acc;
+        
+    acc(2);
+    acc(7);
+    acc(4);
+    acc(9);
+    acc(3);
+    
+    BOOST_CHECK_EQUAL( mean(acc), 5 );
+    BOOST_CHECK_EQUAL( moment<2>(acc), 159./5. );
+    BOOST_CHECK_EQUAL( moment<3>(acc), 1171./5. );
+    BOOST_CHECK_EQUAL( moment<4>(acc), 1863 );
+    BOOST_CHECK_CLOSE( kurtosis(acc), -1.39965397924, 1e-6 );
+
+[*See also]
+
+* [classref boost::accumulators::impl::kurtosis_impl [^kurtosis_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.mean [^mean]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.moment [^moment]]
+
+[endsect]
+
+[section:max max]
+
+Calculates the maximum value of all the samples.
+
+[variablelist
+    [[Result Type] [``
+                    _sample_type_
+                    ``]]
+    [[Depends On] [['none]]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<int, stats<tag::max> > acc;
+
+    acc(1);
+    BOOST_CHECK_EQUAL(1, (max)(acc));
+
+    acc(0);
+    BOOST_CHECK_EQUAL(1, (max)(acc));
+
+    acc(2);
+    BOOST_CHECK_EQUAL(2, (max)(acc));
+
+[*See also]
+
+* [classref boost::accumulators::impl::max_impl [^max_impl]]
+
+[endsect]
+
+[section:mean mean ['and variants]]
+
+Calculates the mean of samples, weights or variates. The calculation is either
+lazy (in the result extractor), or immediate (in the accumulator). The lazy implementation
+is the default. For more implementation details, see 
+[classref boost::accumulators::impl::mean_impl [^mean_impl]] or.
+[classref boost::accumulators::impl::immediate_mean_impl [^immediate_mean_impl]]
+
+[variablelist
+    [[Result Type] [For samples, `numeric::functional::average<_sample_type_, std::size_t>::result_type` \n
+                    For weights, `numeric::functional::average<_weight_type_, std::size_t>::result_type` \n
+                    For variates, `numeric::functional::average<_variate_type_, std::size_t>::result_type`]]
+    [[Depends On] [`count` \n
+                   The lazy mean of samples depends on `sum` \n
+                   The lazy mean of weights depends on `sum_of_weights` \n
+                   The lazy mean of variates depends on `sum_of_variates<>`]]
+    [[Variants] [`mean_of_weights` \n
+                 `mean_of_variates<_variate_type_, _variate_tag_>` \n
+                 `immediate_mean` \n
+                 `immediate_mean_of_weights` \n
+                 `immediate_mean_of_variates<_variate_type_, _variate_tag_>`]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<
+        int
+      , stats<
+            tag::mean
+          , tag::mean_of_weights
+          , tag::mean_of_variates<int, tag::covariate1>
+        >
+      , int 
+    > acc;
+
+    acc(1, weight = 2, covariate1 = 3);
+    BOOST_CHECK_CLOSE(1., mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc));
+    BOOST_CHECK_EQUAL(2, sum(acc));
+    BOOST_CHECK_CLOSE(2., mean_of_weights(acc), 1e-5);
+    BOOST_CHECK_CLOSE(3., (mean_of_variates<int, tag::covariate1>(acc)), 1e-5);
+
+    acc(0, weight = 4, covariate1 = 4);
+    BOOST_CHECK_CLOSE(0.33333333333333333, mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc));
+    BOOST_CHECK_EQUAL(2, sum(acc));
+    BOOST_CHECK_CLOSE(3., mean_of_weights(acc), 1e-5);
+    BOOST_CHECK_CLOSE(3.5, (mean_of_variates<int, tag::covariate1>(acc)), 1e-5);
+
+    acc(2, weight = 9, covariate1 = 8);
+    BOOST_CHECK_CLOSE(1.33333333333333333, mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(3u, count(acc));
+    BOOST_CHECK_EQUAL(20, sum(acc));
+    BOOST_CHECK_CLOSE(5., mean_of_weights(acc), 1e-5);
+    BOOST_CHECK_CLOSE(5., (mean_of_variates<int, tag::covariate1>(acc)), 1e-5);
+
+    accumulator_set<
+        int
+      , stats<
+            tag::mean(immediate)
+          , tag::mean_of_weights(immediate)
+          , tag::mean_of_variates<int, tag::covariate1>(immediate)
+        >
+      , int
+    > acc2;
+
+    acc2(1, weight = 2, covariate1 = 3);
+    BOOST_CHECK_CLOSE(1., mean(acc2), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc2));
+    BOOST_CHECK_CLOSE(2., mean_of_weights(acc2), 1e-5);
+    BOOST_CHECK_CLOSE(3., (mean_of_variates<int, tag::covariate1>(acc2)), 1e-5);
+        
+    acc2(0, weight = 4, covariate1 = 4);
+    BOOST_CHECK_CLOSE(0.33333333333333333, mean(acc2), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc2));
+    BOOST_CHECK_CLOSE(3., mean_of_weights(acc2), 1e-5);
+    BOOST_CHECK_CLOSE(3.5, (mean_of_variates<int, tag::covariate1>(acc2)), 1e-5);
+    
+    acc2(2, weight = 9, covariate1 = 8);
+    BOOST_CHECK_CLOSE(1.33333333333333333, mean(acc2), 1e-5);
+    BOOST_CHECK_EQUAL(3u, count(acc2));
+    BOOST_CHECK_CLOSE(5., mean_of_weights(acc2), 1e-5);
+    BOOST_CHECK_CLOSE(5., (mean_of_variates<int, tag::covariate1>(acc2)), 1e-5);
+
+[*See also]
+
+* [classref boost::accumulators::impl::mean_impl [^mean_impl]]
+* [classref boost::accumulators::impl::immediate_mean_impl [^immediate_mean_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.sum [^sum]]
+
+[endsect]
+
+[section:median median ['and variants]]
+
+Median estimation based on the [^P^2] quantile estimator, the density estimator, or
+the [^P^2] cumulative distribution estimator. For more implementation details, see
+[classref boost::accumulators::impl::median_impl [^median_impl]], 
+[classref boost::accumulators::impl::with_density_median_impl [^with_density_median_impl]], 
+and [classref boost::accumulators::impl::with_p_square_cumulative_distribution_median_impl [^with_p_square_cumulative_distribution_median_impl]].
+
+The three median accumulators all satisfy the `tag::median` feature, and can all be
+extracted with the `median()` extractor.
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, std::size_t>::result_type
+                    ``]]
+    [[Depends On] [`median` depends on `p_square_quantile_for_median` \n
+                   `with_density_median` depends on `count` and `density` \n
+                   `with_p_square_cumulative_distribution_median` depends on `p_square_cumulative_distribution`]]
+    [[Variants] [`with_density_median` \n
+                 `with_p_square_cumulative_distribution_median`]]
+    [[Initialization Parameters] [`with_density_median` requires `tag::density::cache_size` and `tag::density::num_bins` \n
+                                  `with_p_square_cumulative_distribution_median` requires `tag::p_square_cumulative_distribution::num_cells`]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [TODO]] 
+]
+
+[*Example]
+
+    // two random number generators
+    double mu = 1.;
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(mu,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> >
+        normal(rng, mean_sigma);
+    
+    accumulator_set<double, stats<tag::median(with_p_square_quantile) > > acc;
+    accumulator_set<double, stats<tag::median(with_density) > > 
+        acc_dens( density_cache_size = 10000, density_num_bins = 1000 );
+    accumulator_set<double, stats<tag::median(with_p_square_cumulative_distribution) > > 
+        acc_cdist( p_square_cumulative_distribution_num_cells = 100 );
+        
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        double sample = normal();
+        acc(sample);
+        acc_dens(sample);
+        acc_cdist(sample);
+    }
+    
+    BOOST_CHECK_CLOSE(1., median(acc), 1.);
+    BOOST_CHECK_CLOSE(1., median(acc_dens), 1.);
+    BOOST_CHECK_CLOSE(1., median(acc_cdist), 3.);
+
+[*See also]
+
+* [classref boost::accumulators::impl::median_impl [^median_impl]]
+* [classref boost::accumulators::impl::with_density_median_impl [^with_density_median_impl]]
+* [classref boost::accumulators::impl::with_p_square_cumulative_distribution_median_impl [^with_p_square_cumulative_distribution_median_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.p_square_quantile [^p_square_quantile]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.p_square_cumulative_distribution [^p_square_cumulative_distribution]]
+
+[endsect]
+
+[section:min min]
+
+Calculates the minimum value of all the samples.
+
+[variablelist
+    [[Result Type] [``
+                    _sample_type_
+                    ``]]
+    [[Depends On] [['none]]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<int, stats<tag::min> > acc;
+
+    acc(1);
+    BOOST_CHECK_EQUAL(1, (min)(acc));
+
+    acc(0);
+    BOOST_CHECK_EQUAL(0, (min)(acc));
+
+    acc(2);
+    BOOST_CHECK_EQUAL(0, (min)(acc));
+
+[*See also]
+
+* [classref boost::accumulators::impl::min_impl [^min_impl]]
+
+[endsect]
+
+[section:moment moment]
+
+Calculates the N-th moment of the samples, which is defined as the sum of the N-th power of the
+samples over the count of samples.
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, std::size_t>::result_type
+                    ``]]
+    [[Depends On] [`count`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<int, stats<tag::moment<2> > > acc1;
+
+    acc1(2); //    4
+    acc1(4); //   16
+    acc1(5); // + 25
+             // = 45 / 3 = 15
+
+    BOOST_CHECK_CLOSE(15., moment<2>(acc1), 1e-5);
+
+    accumulator_set<int, stats<tag::moment<5> > > acc2;
+
+    acc2(2); //     32
+    acc2(3); //    243
+    acc2(4); //   1024
+    acc2(5); // + 3125
+             // = 4424 / 4 = 1106
+
+    BOOST_CHECK_CLOSE(1106., moment<5>(acc2), 1e-5);
+
+[*See also]
+
+* [classref boost::accumulators::impl::moment_impl [^moment_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+
+[endsect]
+
+[section:p_square_cumulative_distribution p_square_cumulative_distribution]
+
+Histogram calculation of the cumulative distribution with the [^P^2] algorithm.
+For more implementation details, see 
+[classref boost::accumulators::impl::p_square_cumulative_distribution_impl [^p_square_cumulative_distribution_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    iterator_range<
+                        std::vector<
+                            std::pair<
+                                numeric::functional::average<_sample_type_, std::size_t>::result_type
+                              , numeric::functional::average<_sample_type_, std::size_t>::result_type
+                            >
+                        >::iterator
+                    >
+                    ``]]
+    [[Depends On] [`count`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [`tag::p_square_cumulative_distribution::num_cells`]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [O(N) where N is `num_cells`]] 
+]
+
+[*Example]
+
+    // tolerance in %
+    double epsilon = 3;
+
+    typedef accumulator_set<double, stats<tag::p_square_cumulative_distribution> > accumulator_t;
+        
+    accumulator_t acc(tag::p_square_cumulative_distribution::num_cells = 100);
+    
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(0,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+    
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        acc(normal());
+    }
+    
+    typedef iterator_range<std::vector<std::pair<double, double> >::iterator > histogram_type;
+    histogram_type histogram = p_square_cumulative_distribution(acc);
+    
+    for (std::size_t i = 0; i < histogram.size(); ++i)
+    {   
+        // problem with small results: epsilon is relative (in percent), not absolute!
+        if ( histogram[i].second > 0.001 )    
+            BOOST_CHECK_CLOSE( 0.5 * (1.0 + erf( histogram[i].first / sqrt(2.0) )), histogram[i].second, epsilon );
+    }        
+
+[*See also]
+
+* [classref boost::accumulators::impl::p_square_cumulative_distribution_impl [^p_square_cumulative_distribution_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+
+[endsect]
+
+[section:p_square_quantile p_square_quantile ['and variants]]
+
+Single quantile estimation with the [^P^2] algorithm. For more implementation details, see
+[classref boost::accumulators::impl::p_square_quantile_impl [^p_square_quantile_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, std::size_t>::result_type
+                    ``]]
+    [[Depends On] [`count`]]
+    [[Variants] [`p_square_quantile_for_median`]]
+    [[Initialization Parameters] [`quantile_probability`, which defaults to `0.5`.
+                                  (Note: for `p_square_quantile_for_median`, the `quantile_probability`
+                                  parameter is ignored and is always `0.5`.)]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    typedef accumulator_set<double, stats<tag::p_square_quantile> > accumulator_t;
+
+    // tolerance in %
+    double epsilon = 1;
+    
+    // a random number generator
+    boost::lagged_fibonacci607 rng;
+    
+    accumulator_t acc0(quantile_probability = 0.001);
+    accumulator_t acc1(quantile_probability = 0.01 );
+    accumulator_t acc2(quantile_probability = 0.1  );
+    accumulator_t acc3(quantile_probability = 0.25 );
+    accumulator_t acc4(quantile_probability = 0.5  );
+    accumulator_t acc5(quantile_probability = 0.75 );
+    accumulator_t acc6(quantile_probability = 0.9  );
+    accumulator_t acc7(quantile_probability = 0.99 );
+    accumulator_t acc8(quantile_probability = 0.999);
+    
+    for (int i=0; i<100000; ++i)
+    {
+        double sample = rng();
+        acc0(sample);
+        acc1(sample);
+        acc2(sample);
+        acc3(sample);
+        acc4(sample);
+        acc5(sample);
+        acc6(sample);
+        acc7(sample);
+        acc8(sample);
+    }
+    
+    BOOST_CHECK_CLOSE( p_square_quantile(acc0), 0.001, 15*epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc1), 0.01 , 5*epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc2), 0.1  , epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc3), 0.25 , epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc4), 0.5  , epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc5), 0.75 , epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc6), 0.9  , epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc7), 0.99 , epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc8), 0.999, epsilon );    
+
+[*See also]
+
+* [classref boost::accumulators::impl::p_square_quantile_impl [^p_square_quantile_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+
+[endsect]
+
+[section:peaks_over_threshold peaks_over_threshold ['and variants]]
+
+Peaks Over Threshold method for quantile and tail mean estimation. For implementation
+details, see [classref boost::accumulators::impl::peaks_over_threshold_impl [^peaks_over_threshold_impl]]
+and [classref boost::accumulators::impl::peaks_over_threshold_prob_impl [^peaks_over_threshold_prob_impl]].
+
+Both `tag::peaks_over_threshold` and `tag::peaks_over_threshold_prob<>` satisfy the `tag::abstract_peaks_over_threshold`
+feature, and can be extracted with the `peaks_over_threshold()` extractor. The result is a 3-tuple representing
+the fit parameters `u_bar`, `beta_bar` and `xi_hat`.
+
+[variablelist
+    [[Result Type] [``
+                    boost::tuple<
+                        numeric::functional::average<_sample_type_, std::size_t>::result_type // u_bar
+                      , numeric::functional::average<_sample_type_, std::size_t>::result_type // beta_bar
+                      , numeric::functional::average<_sample_type_, std::size_t>::result_type // xi_hat
+                    >
+                    ``]]
+    [[Depends On] [`count` \n
+                   In addtion, `tag::peaks_over_threshold_prob<>` depends on `tail<_left_or_right_>`]]
+    [[Variants] [`peaks_over_threshold_prob<_left_or_right_>`]]
+    [[Initialization Parameters] [ `tag::peaks_over_threshold::threshold_value` \n
+                                   `tag::peaks_over_threshold_prob::threshold_probability` \n
+                                   `tag::tail<_left_or_right_>::cache_size` ]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [TODO]] 
+]
+
+[*Example]
+
+See example for [link accumulators.user_s_guide.the_statistical_accumulators_library.pot_quantile [^pot_quantile]].
+
+[*See also]
+
+* [classref boost::accumulators::impl::peaks_over_threshold_impl [^peaks_over_threshold_impl]]
+* [classref boost::accumulators::impl::peaks_over_threshold_prob_impl [^peaks_over_threshold_prob_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.tail [^tail]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.pot_quantile [^pot_quantile]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.pot_tail_mean [^pot_tail_mean]]
+
+[endsect]
+
+[section:pot_quantile pot_quantile ['and variants]]
+
+Quantile estimation based on Peaks over Threshold method (for both left and right tails). For 
+implementation details, see [classref boost::accumulators::impl::pot_quantile_impl [^pot_quantile_impl]].
+
+Both `tag::pot_quantile<_left_or_right_>` and `tag::pot_quantile_prob<_left_or_right_>` satisfy the
+`tag::quantile` feature and can be extracted using the `quantile()` extractor.
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, std::size_t>::result_type
+                    ``]]
+    [[Depends On] [`pot_quantile<_left_or_right_>` depends on `peaks_over_threshold<_left_or_right_>` \n
+                   `pot_quantile_prob<_left_or_right_>` depends on `peaks_over_threshold_prob<_left_or_right_>` ]]
+    [[Variants] [`pot_quantile_prob<_left_or_right_>`]]
+    [[Initialization Parameters] [ `tag::peaks_over_threshold::threshold_value` \n
+                                   `tag::peaks_over_threshold_prob::threshold_probability` \n
+                                   `tag::tail<_left_or_right_>::cache_size` ]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [`quantile_probability`]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [TODO]] 
+]
+
+[*Example]
+
+    // tolerance in %
+    double epsilon = 1.;
+
+    double alpha = 0.999;
+    double threshold_probability = 0.99;
+    double threshold = 3.;
+    
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(0,1);
+    boost::exponential_distribution<> lambda(1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::exponential_distribution<> > exponential(rng, lambda);
+    
+    accumulator_set<double, stats<tag::pot_quantile<right>(with_threshold_value)> > acc1(
+        tag::peaks_over_threshold::threshold_value = threshold
+    );
+    accumulator_set<double, stats<tag::pot_quantile<right>(with_threshold_probability)> > acc2(
+        tag::tail<right>::cache_size = 2000
+      , tag::peaks_over_threshold_prob::threshold_probability = threshold_probability
+    );
+    
+    threshold_probability = 0.995;
+    threshold = 5.;
+    
+    accumulator_set<double, stats<tag::pot_quantile<right>(with_threshold_value)> > acc3(
+        tag::peaks_over_threshold::threshold_value = threshold
+    );
+    accumulator_set<double, stats<tag::pot_quantile<right>(with_threshold_probability)> > acc4(
+        tag::tail<right>::cache_size = 2000
+      , tag::peaks_over_threshold_prob::threshold_probability = threshold_probability
+    );
+    
+    for (std::size_t i = 0; i < 100000; ++i)
+    {
+        double sample = normal();
+        acc1(sample);
+        acc2(sample);
+    }
+    
+    for (std::size_t i = 0; i < 100000; ++i)
+    {
+        double sample = exponential();
+        acc3(sample);
+        acc4(sample);
+    }
+    
+    BOOST_CHECK_CLOSE( quantile(acc1, quantile_probability = alpha), 3.090232, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability = alpha), 3.090232, epsilon );  
+    
+    BOOST_CHECK_CLOSE( quantile(acc3, quantile_probability = alpha), 6.908, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc4, quantile_probability = alpha), 6.908, epsilon );  
+
+[*See also]
+
+* [classref boost::accumulators::impl::pot_quantile_impl [^pot_quantile_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.peaks_over_threshold [^peaks_over_threshold]]
+
+[endsect]
+
+[section:pot_tail_mean pot_tail_mean]
+
+Estimation of the (coherent) tail mean based on the peaks over threshold method (for both left and right tails).
+For inplementation details, see [classref boost::accumulators::impl::pot_tail_mean_impl [^pot_tail_mean_impl]].
+
+Both `tag::pot_tail_mean<_left_or_right_>` and `tag::pot_tail_mean_prob<_left_or_right_>` satisfy the
+`tag::tail_mean` feature and can be extracted using the `tail_mean()` extractor.
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, std::size_t>::result_type
+                    ``]]
+    [[Depends On] [`pot_tail_mean<_left_or_right_>` depends on `peaks_over_threshold<_left_or_right_>`
+                         and `pot_quantile<_left_or_right_>` \n
+                   `pot_tail_mean_prob<_left_or_right_>` depends on `peaks_over_threshold_prob<_left_or_right_>`
+                         and `pot_quantile_prob<_left_or_right_>` ]]
+    [[Variants] [`pot_tail_mean_prob<_left_or_right_>`]]
+    [[Initialization Parameters] [ `tag::peaks_over_threshold::threshold_value` \n
+                                   `tag::peaks_over_threshold_prob::threshold_probability` \n
+                                   `tag::tail<_left_or_right_>::cache_size` ]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [`quantile_probability`]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [TODO]] 
+]
+
+[*Example]
+
+    // TODO
+
+[*See also]
+
+* [classref boost::accumulators::impl::pot_tail_mean_impl [^pot_tail_mean_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.peaks_over_threshold [^peaks_over_threshold]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.pot_quantile [^pot_quantile]]
+
+[endsect]
+
+[section:skewness skewness]
+
+The skewness of a sample distribution is defined as the ratio of the 3rd central moment and the [^3/2]-th power 
+of the 2nd central moment (the variance) of the sampless 3. For implementation details, see
+[classref boost::accumulators::impl::skewness_impl [^skewness_impl]].
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, _sample_type_>::result_type
+                    ``]]
+    [[Depends On] [`mean` \n `moment<2>` \n `moment<3>`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<int, stats<tag::skewness > > acc2;
+    
+    acc2(2);
+    acc2(7);
+    acc2(4);
+    acc2(9);
+    acc2(3);
+    
+    BOOST_CHECK_EQUAL( mean(acc2), 5 );
+    BOOST_CHECK_EQUAL( moment<2>(acc2), 159./5. );
+    BOOST_CHECK_EQUAL( moment<3>(acc2), 1171./5. );
+    BOOST_CHECK_CLOSE( skewness(acc2), 0.406040288214, 1e-6 );
+
+
+[*See also]
+
+* [classref boost::accumulators::impl::skewness_impl [^skewness_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.mean [^mean]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.moment [^moment]]
+
+[endsect]
+
+[section:sum sum ['and variants]]
+
+For summing the samples, weights or variates. 
+
+[variablelist
+    [[Result Type] [`_sample_type_` for summing samples \n
+                    `_weight_type_` for summing weights \n
+                    `_variate_type_` for summing variates]]
+    [[Depends On] [['none]]]
+    [[Variants] [`tag::sum` \n
+                 `tag::sum_of_weights` \n
+                 `tag::sum_of_variates<_variate_type_, _variate_tag_>`]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [`weight` for summing weights \n
+                               `_variate_tag_` for summing variates]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<
+        int
+      , stats<
+            tag::sum
+          , tag::sum_of_weights
+          , tag::sum_of_variates<int, tag::covariate1>
+        >
+      , int
+    > acc;
+
+    acc(1, weight = 2, covariate1 = 3);
+    BOOST_CHECK_EQUAL(2, sum(acc));  // weighted sample = 1 * 2
+    BOOST_CHECK_EQUAL(2, sum_of_weights(acc));
+    BOOST_CHECK_EQUAL(3, sum_of_variates(acc));
+
+    acc(2, weight = 4, covariate1 = 6);
+    BOOST_CHECK_EQUAL(10, sum(acc)); // weighted sample = 2 * 4
+    BOOST_CHECK_EQUAL(6, sum_of_weights(acc));
+    BOOST_CHECK_EQUAL(9, sum_of_variates(acc));
+
+    acc(3, weight = 6, covariate1 = 9);
+    BOOST_CHECK_EQUAL(28, sum(acc)); // weighted sample = 3 * 6
+    BOOST_CHECK_EQUAL(12, sum_of_weights(acc));
+    BOOST_CHECK_EQUAL(18, sum_of_variates(acc));
+
+[*See also]
+
+* [classref boost::accumulators::impl::sum_impl [^sum_impl]]
+
+[endsect]
+
+[section:tail tail]
+
+Tracks the largest or smallest [^N] values. `tag::tail<right>` tracks the largest [^N],
+and `tag::tail<left>` tracks the smallest. The parameter [^N] is specified with the
+`tag::tail<_left_or_right_>::cache_size` initialization parameter. For implementation details, see
+[classref boost::accumulators::impl::tail_impl [^tail_impl]].
+
+Both `tag::tail<left>` and `tag::tail<right>` satisfy the `tag::abstract_tail` feature and 
+can be extracted with the `tail()` extractor.
+
+[variablelist
+    [[Result Type] [``
+                    boost::iterator_range<
+                        boost::reverse_iterator<
+                            boost::permutation_iterator<
+                                std::vector<_sample_type_>::const_iterator  // samples
+                              , std::vector<std::size_t>::iterator          // indices
+                            >
+                        >
+                    >
+                    ``]]
+    [[Depends On] [['none]]]
+    [[Variants] [`abstract_tail`]]
+    [[Initialization Parameters] [`tag::tail<_left_or_right_>::cache_size`]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(log N), where N is the cache size]] 
+    [[Extractor Complexity] [O(N log N), where N is the cache size]] 
+]
+
+[*Example]
+
+See the Example for [link accumulators.user_s_guide.the_statistical_accumulators_library.tail_variate [^tail_variate]].
+
+[*See also]
+
+* [classref boost::accumulators::impl::tail_impl [^tail_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.tail_variate [^tail_variate]]
+
+[endsect]
+
+[section:coherent_tail_mean coherent_tail_mean]
+
+Estimation of the coherent tail mean based on order statistics (for both left and right tails).
+The left coherent tail mean feature is `tag::coherent_tail_mean<left>`, and the right choherent
+tail mean feature is `tag::coherent_tail_mean<right>`. They both share the `tag::tail_mean` feature
+and can be extracted with the `tail_mean()` extractor. For more implementation details, see
+[classref boost::accumulators::impl::coherent_tail_mean_impl [^coherent_tail_mean_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, std::size_t>::result_type
+                    ``]]
+    [[Depends On] [`count` \n `quantile` \n `non_coherent_tail_mean<_left_or_right_>`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [`tag::tail<_left_or_right_>::cache_size`]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [`quantile_probability`]]
+    [[Accumulator Complexity] [O(log N), where N is the cache size]] 
+    [[Extractor Complexity] [O(N log N), where N is the cache size]] 
+]
+
+[*Example]
+
+See the example for 
+[link accumulators.user_s_guide.the_statistical_accumulators_library.non_coherent_tail_mean [^non_coherent_tail_mean]].
+
+[*See also]
+
+* [classref boost::accumulators::impl::coherent_tail_mean_impl [^coherent_tail_mean_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.extended_p_square_quantile [^extended_p_square_quantile]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.pot_quantile [^pot_quantile]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.tail_quantile [^tail_quantile]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.non_coherent_tail_mean [^non_coherent_tail_mean]]
+
+[endsect]
+
+[section:non_coherent_tail_mean non_coherent_tail_mean]
+
+Estimation of the (non-coherent) tail mean based on order statistics (for both left and right tails).
+The left non-coherent tail mean feature is `tag::non_coherent_tail_mean<left>`, and the right non-choherent
+tail mean feature is `tag::non_coherent_tail_mean<right>`. They both share the `tag::abstract_non_coherent_tail_mean`
+feature and can be extracted with the `non_coherent_tail_mean()` extractor. For more implementation details, see
+[classref boost::accumulators::impl::non_coherent_tail_mean_impl [^non_coherent_tail_mean_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, std::size_t>::result_type
+                    ``]]
+    [[Depends On] [`count` \n `tail<_left_or_right_>`]]
+    [[Variants] [`abstract_non_coherent_tail_mean`]]
+    [[Initialization Parameters] [`tag::tail<_left_or_right_>::cache_size`]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [`quantile_probability`]]
+    [[Accumulator Complexity] [O(log N), where N is the cache size]] 
+    [[Extractor Complexity] [O(N log N), where N is the cache size]] 
+]
+
+[*Example]
+
+    // tolerance in %
+    double epsilon = 1;
+    
+    std::size_t n = 100000; // number of MC steps
+    std::size_t c =  10000; // cache size
+    
+    typedef accumulator_set<double, stats<tag::non_coherent_tail_mean<right>, tag::tail_quantile<right> > > accumulator_t_right1;
+    typedef accumulator_set<double, stats<tag::non_coherent_tail_mean<left>, tag::tail_quantile<left> > > accumulator_t_left1;
+    typedef accumulator_set<double, stats<tag::coherent_tail_mean<right>, tag::tail_quantile<right> > > accumulator_t_right2;
+    typedef accumulator_set<double, stats<tag::coherent_tail_mean<left>, tag::tail_quantile<left> > > accumulator_t_left2;
+    
+    accumulator_t_right1 acc0( right_tail_cache_size = c );
+    accumulator_t_left1 acc1( left_tail_cache_size = c );
+    accumulator_t_right2 acc2( right_tail_cache_size = c );
+    accumulator_t_left2 acc3( left_tail_cache_size = c );
+    
+    // a random number generator
+    boost::lagged_fibonacci607 rng;
+    
+    for (std::size_t i = 0; i < n; ++i)
+    {
+        double sample = rng();
+        acc0(sample);
+        acc1(sample);
+        acc2(sample);
+        acc3(sample);
+    }
+    
+    // check uniform distribution
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc0, quantile_probability = 0.95), 0.975, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc0, quantile_probability = 0.975), 0.9875, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc0, quantile_probability = 0.99), 0.995, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc0, quantile_probability = 0.999), 0.9995, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc1, quantile_probability = 0.05), 0.025, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc1, quantile_probability = 0.025), 0.0125, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc1, quantile_probability = 0.01), 0.005, 5 );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc1, quantile_probability = 0.001), 0.0005, 10 );
+    BOOST_CHECK_CLOSE( tail_mean(acc2, quantile_probability = 0.95), 0.975, epsilon );
+    BOOST_CHECK_CLOSE( tail_mean(acc2, quantile_probability = 0.975), 0.9875, epsilon );
+    BOOST_CHECK_CLOSE( tail_mean(acc2, quantile_probability = 0.99), 0.995, epsilon );
+    BOOST_CHECK_CLOSE( tail_mean(acc2, quantile_probability = 0.999), 0.9995, epsilon );
+    BOOST_CHECK_CLOSE( tail_mean(acc3, quantile_probability = 0.05), 0.025, epsilon );
+    BOOST_CHECK_CLOSE( tail_mean(acc3, quantile_probability = 0.025), 0.0125, epsilon );
+    BOOST_CHECK_CLOSE( tail_mean(acc3, quantile_probability = 0.01), 0.005, 5 );
+    BOOST_CHECK_CLOSE( tail_mean(acc3, quantile_probability = 0.001), 0.0005, 10 );
+
+[*See also]
+
+* [classref boost::accumulators::impl::non_coherent_tail_mean_impl [^non_coherent_tail_mean_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.tail [^tail]]
+
+[endsect]
+
+[section:tail_quantile tail_quantile]
+
+Tail quantile estimation based on order statistics (for both left and right tails).
+The left tail quantile feature is `tag::tail_quantile<left>`, and the right
+tail quantile feature is `tag::tail_quantile<right>`. They both share the `tag::quantile`
+feature and can be extracted with the `quantile()` extractor. For more implementation details, see
+[classref boost::accumulators::impl::tail_quantile_impl [^tail_quantile_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    _sample_type_
+                    ``]]
+    [[Depends On] [`count` \n `tail<_left_or_right_>`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [`tag::tail<_left_or_right_>::cache_size`]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [`quantile_probability`]]
+    [[Accumulator Complexity] [O(log N), where N is the cache size]] 
+    [[Extractor Complexity] [O(N log N), where N is the cache size]] 
+]
+
+[*Example]
+
+    // tolerance in %
+    double epsilon = 1;
+    
+    std::size_t n = 100000; // number of MC steps
+    std::size_t c =  10000; // cache size
+        
+    typedef accumulator_set<double, stats<tag::tail_quantile<right> > > accumulator_t_right;
+    typedef accumulator_set<double, stats<tag::tail_quantile<left> > > accumulator_t_left;
+    
+    accumulator_t_right acc0( tag::tail<right>::cache_size = c );
+    accumulator_t_right acc1( tag::tail<right>::cache_size = c );
+    accumulator_t_left  acc2( tag::tail<left>::cache_size = c );
+    accumulator_t_left  acc3( tag::tail<left>::cache_size = c );
+    
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(0,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+                    
+    for (std::size_t i = 0; i < n; ++i)
+    {
+        double sample1 = rng();
+        double sample2 = normal();
+        acc0(sample1);
+        acc1(sample2);
+        acc2(sample1);
+        acc3(sample2);
+    }
+    
+    // check uniform distribution
+    BOOST_CHECK_CLOSE( quantile(acc0, quantile_probability = 0.95 ), 0.95,  epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc0, quantile_probability = 0.975), 0.975, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc0, quantile_probability = 0.99 ), 0.99,  epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc0, quantile_probability = 0.999), 0.999, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability  = 0.05 ), 0.05,  2 );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability  = 0.025), 0.025, 2 );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability  = 0.01 ), 0.01,  3 );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability  = 0.001), 0.001, 20 );
+    
+    // check standard normal distribution
+    BOOST_CHECK_CLOSE( quantile(acc1, quantile_probability = 0.975),  1.959963, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc1, quantile_probability = 0.999),  3.090232, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc3, quantile_probability  = 0.025), -1.959963, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc3, quantile_probability  = 0.001), -3.090232, epsilon );
+
+[*See also]
+
+* [classref boost::accumulators::impl::tail_quantile_impl [^tail_quantile_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.tail [^tail]]
+
+[endsect]
+
+[section:tail_variate tail_variate]
+
+Tracks the covariates of largest or smallest [^N] samples. 
+`tag::tail_variate<_variate_type_, _variate_tag_, right>` tracks the covariate associated with 
+_variate_tag_ for the largest [^N], and `tag::tail_variate<_variate_type_, _variate_tag_, left>`
+for the smallest. The parameter [^N] is specified with the `tag::tail<_left_or_right_>::cache_size` 
+initialization parameter. For implementation details, see
+[classref boost::accumulators::impl::tail_variate_impl [^tail_variate_impl]].
+
+Both `tag::tail_variate<_variate_type_, _variate_tag_, right>` and 
+`tag::tail_variate<_variate_type_, _variate_tag_, left>` satisfy the `tag::abstract_tail_variate` feature
+and can be extracted with the `tail_variate()` extractor.
+
+[variablelist
+    [[Result Type] [``
+                    boost::iterator_range<
+                        boost::reverse_iterator<
+                            boost::permutation_iterator<
+                                std::vector<_variate_type_>::const_iterator // variates
+                              , std::vector<std::size_t>::iterator          // indices
+                            >
+                        >
+                    >
+                    ``]]
+    [[Depends On] [`tail<_left_or_right_>`]]
+    [[Variants] [`abstract_tail_variate`]]
+    [[Initialization Parameters] [`tag::tail<_left_or_right_>::cache_size`]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(log N), where N is the cache size]] 
+    [[Extractor Complexity] [O(N log N), where N is the cache size]] 
+]
+
+[*Example]
+
+    accumulator_set<int, stats<tag::tail_variate<int, tag::covariate1, right> > > acc(
+        tag::tail<right>::cache_size = 4
+    );
+    
+    acc(8, covariate1 = 3);
+    CHECK_RANGE_EQUAL(tail(acc), {8});
+    CHECK_RANGE_EQUAL(tail_variate(acc), {3});
+    
+    acc(16, covariate1 = 1);
+    CHECK_RANGE_EQUAL(tail(acc), {16, 8});
+    CHECK_RANGE_EQUAL(tail_variate(acc), {1, 3});
+
+    acc(12, covariate1 = 4);
+    CHECK_RANGE_EQUAL(tail(acc), {16, 12, 8});
+    CHECK_RANGE_EQUAL(tail_variate(acc), {1, 4, 3});
+
+    acc(24, covariate1 = 5);
+    CHECK_RANGE_EQUAL(tail(acc), {24, 16, 12, 8});
+    CHECK_RANGE_EQUAL(tail_variate(acc), {5, 1, 4, 3});
+
+    acc(1, covariate1 = 9);
+    CHECK_RANGE_EQUAL(tail(acc), {24, 16, 12, 8});
+    CHECK_RANGE_EQUAL(tail_variate(acc), {5, 1, 4, 3});
+
+    acc(9, covariate1 = 7);
+    CHECK_RANGE_EQUAL(tail(acc), {24,  16, 12, 9});
+    CHECK_RANGE_EQUAL(tail_variate(acc), {5, 1, 4, 7});
+
+[*See also]
+
+* [classref boost::accumulators::impl::tail_variate_impl [^tail_variate_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.tail [^tail]]
+
+[endsect]
+
+[section:tail_variate_means tail_variate_means ['and variants]]
+
+Estimation of the absolute and relative tail variate means (for both left and right tails).
+The absolute tail variate means has the feature 
+`tag::absolute_tail_variate_means<_left_or_right_, _variate_type_, _variate_tag_>`
+and the relative tail variate mean has the feature
+`tag::relative_tail_variate_means<_left_or_right_, _variate_type_, _variate_tag_>`. All
+absolute tail variate mean features share the `tag::abstract_absolute_tail_variate_means`
+feature and can be extracted with the `tail_variate_means()` extractor. All the
+relative tail variate mean features share the `tag::abstract_relative_tail_variate_means`
+feature and can be extracted with the `relative_tail_variate_means()` extractor.
+
+For more implementation details, see
+[classref boost::accumulators::impl::tail_variate_means_impl [^tail_variate_means_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    boost::iterator_range<
+                        std::vector<
+                            numeric::functional::average<_sample_type_, std::size_t>::result_type
+                        >::iterator
+                    >
+                    ``]]
+    [[Depends On] [`non_coherent_tail_mean<_left_or_right_>` \n 
+                   `tail_variate<_variate_type_, _variate_tag_, _left_or_right_>`]]
+    [[Variants] [`tag::absolute_tail_variate_means<_left_or_right_, _variate_type_, _variate_tag_>` \n
+                 `tag::relative_tail_variate_means<_left_or_right_, _variate_type_, _variate_tag_>`]]
+    [[Initialization Parameters] [`tag::tail<_left_or_right_>::cache_size`]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [`quantile_probability`]]
+    [[Accumulator Complexity] [O(log N), where N is the cache size]] 
+    [[Extractor Complexity] [O(N log N), where N is the cache size]] 
+]
+
+[*Example]
+
+    std::size_t c = 5; // cache size
+    
+    typedef double variate_type;
+    typedef std::vector<variate_type> variate_set_type;
+    
+    typedef accumulator_set<double, stats<
+        tag::tail_variate_means<right, variate_set_type, tag::covariate1>(relative)>, tag::tail<right> >
+    accumulator_t1;
+    
+    typedef accumulator_set<double, stats<
+        tag::tail_variate_means<right, variate_set_type, tag::covariate1>(absolute)>, tag::tail<right> >
+    accumulator_t2;
+    
+    typedef accumulator_set<double, stats<
+        tag::tail_variate_means<left, variate_set_type, tag::covariate1>(relative)>, tag::tail<left> >
+    accumulator_t3;
+    
+    typedef accumulator_set<double, stats<
+        tag::tail_variate_means<left, variate_set_type, tag::covariate1>(absolute)>, tag::tail<left> >
+    accumulator_t4;
+    
+    accumulator_t1 acc1( right_tail_cache_size = c );
+    accumulator_t2 acc2( right_tail_cache_size = c );
+    accumulator_t3 acc3( left_tail_cache_size = c );
+    accumulator_t4 acc4( left_tail_cache_size = c );
+    
+    variate_set_type cov1, cov2, cov3, cov4, cov5;
+    double c1[] = { 10., 20., 30., 40. }; // 100
+    double c2[] = { 26.,  4., 17.,  3. }; // 50
+    double c3[] = { 46., 64., 40., 50. }; // 200
+    double c4[] = {  1.,  3., 70.,  6. }; // 80
+    double c5[] = {  2.,  2.,  2., 14. }; // 20
+    cov1.assign(c1, c1 + sizeof(c1)/sizeof(variate_type));
+    cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type));
+    cov3.assign(c3, c3 + sizeof(c3)/sizeof(variate_type));
+    cov4.assign(c4, c4 + sizeof(c4)/sizeof(variate_type));
+    cov5.assign(c5, c5 + sizeof(c5)/sizeof(variate_type));            
+    
+    acc1(100., covariate1 = cov1);
+    acc1( 50., covariate1 = cov2);
+    acc1(200., covariate1 = cov3);
+    acc1( 80., covariate1 = cov4);
+    acc1( 20., covariate1 = cov5);
+    
+    acc2(100., covariate1 = cov1);
+    acc2( 50., covariate1 = cov2);
+    acc2(200., covariate1 = cov3);
+    acc2( 80., covariate1 = cov4);
+    acc2( 20., covariate1 = cov5);
+    
+    acc3(100., covariate1 = cov1);
+    acc3( 50., covariate1 = cov2);
+    acc3(200., covariate1 = cov3);
+    acc3( 80., covariate1 = cov4);
+    acc3( 20., covariate1 = cov5);
+    
+    acc4(100., covariate1 = cov1);
+    acc4( 50., covariate1 = cov2);
+    acc4(200., covariate1 = cov3);
+    acc4( 80., covariate1 = cov4);
+    acc4( 20., covariate1 = cov5);
+   
+    // check relative risk contributions
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.7).begin()     ), 14./75. ); // (10 + 46) / 300 = 14/75
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.7).begin() + 1),  7./25. ); // (20 + 64) / 300 =  7/25
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.7).begin() + 2),  7./30. ); // (30 + 40) / 300 =  7/30
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.7).begin() + 3),  3./10. ); // (40 + 50) / 300 =  3/10
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.3).begin()    ), 14./35. ); // (26 +  2) /  70 = 14/35
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.3).begin() + 1),  3./35. ); // ( 4 +  2) /  70 =  3/35
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.3).begin() + 2), 19./70. ); // (17 +  2) /  70 = 19/70
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.3).begin() + 3), 17./70. ); // ( 3 + 14) /  70 = 17/70
+    
+    // check absolute risk contributions
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.7).begin()    ), 28 ); // (10 + 46) / 2 = 28
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.7).begin() + 1), 42 ); // (20 + 64) / 2 = 42
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.7).begin() + 2), 35 ); // (30 + 40) / 2 = 35
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.7).begin() + 3), 45 ); // (40 + 50) / 2 = 45
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.3).begin()    ), 14 ); // (26 +  2) / 2 = 14
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.3).begin() + 1),  3 ); // ( 4 +  2) / 2 =  3
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.3).begin() + 2),9.5 ); // (17 +  2) / 2 =  9.5
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.3).begin() + 3),8.5 ); // ( 3 + 14) / 2 =  8.5
+    
+    // check relative risk contributions
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.9).begin()    ), 23./100. ); // 46/200 = 23/100
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.9).begin() + 1),  8./25.  ); // 64/200 =  8/25
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.9).begin() + 2),  1./5.   ); // 40/200 =  1/5
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.9).begin() + 3),  1./4.   ); // 50/200 =  1/4
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.1).begin()    ),  1./10.  ); //  2/ 20 =  1/10
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.1).begin() + 1),  1./10.  ); //  2/ 20 =  1/10
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.1).begin() + 2),  1./10.  ); //  2/ 20 =  1/10
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.1).begin() + 3),  7./10.  ); // 14/ 20 =  7/10
+    
+    // check absolute risk contributions
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.9).begin()    ), 46 ); // 46
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.9).begin() + 1), 64 ); // 64
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.9).begin() + 2), 40 ); // 40
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.9).begin() + 3), 50 ); // 50
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.1).begin()    ),  2 ); //  2
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.1).begin() + 1),  2 ); //  2
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.1).begin() + 2),  2 ); //  2
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.1).begin() + 3), 14 ); // 14
+
+[*See also]
+
+* [classref boost::accumulators::impl::tail_variate_means_impl [^tail_variate_means_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.non_coherent_tail_mean [^non_coherent_tail_mean]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.tail_variate [^tail_variate]]
+
+[endsect]
+
+[section:variance variance ['and variants]]
+
+Lazy or iterative calculation of the variance. The lazy calculation is associated with the `tag::variance`
+feature, and the iterative calculation with the `tag::immediate_variance` feature. Both can be extracted
+using the `tag::variance()` extractor. For more implementation details, see
+[classref boost::accumulators::impl::variance_impl [^variance_impl]] and
+[classref boost::accumulators::impl::immediate_variance_impl [^immediate_variance_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, std::size_t>::result_type
+                    ``]]
+    [[Depends On] [`tag::variance` depends on `tag::moment<2>` and `tag::mean` \n
+                   `tag::immediate_variance` depends on `tag::count` and `tag::immediate_mean`]]
+    [[Variants] [`tag::variance` (a.k.a. `tag::variance(lazy))` \n
+                 `tag::immediate_variance` (a.k.a. `tag::variance(immediate)`)]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    // basic lazy variance
+    accumulator_set<int, stats<tag::variance > > acc1;
+
+    acc1(1);
+    acc1(2);
+    acc1(3);
+    acc1(4);
+    acc1(5);
+
+    BOOST_CHECK_EQUAL(5u, count(acc1));
+    BOOST_CHECK_CLOSE(3., mean(acc1), 1e-5);
+    BOOST_CHECK_CLOSE(11., moment<2>(acc1), 1e-5);
+    BOOST_CHECK_CLOSE(2., variance(acc1), 1e-5);
+
+    // immediate variance
+    accumulator_set<int, stats<tag::variance(immediate) > > acc2;
+
+    acc2(1);
+    acc2(2);
+    acc2(3);
+    acc2(4);
+    acc2(5);
+
+    BOOST_CHECK_EQUAL(5u, count(acc2));
+    BOOST_CHECK_CLOSE(3., mean(acc2), 1e-5);
+    BOOST_CHECK_CLOSE(2., variance(acc2), 1e-5);
+
+
+[*See also]
+
+* [classref boost::accumulators::impl::variance_impl [^variance_impl]]
+* [classref boost::accumulators::impl::immediate_variance_impl [^immediate_variance_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.mean [^mean]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.moment [^moment]]
+
+[endsect]
+
+[section:weighted_covariance weighted_covariance]
+
+An iterative Monte Carlo estimator for the weighted covariance. The feature is specified as
+`tag::weighted_covariance<_variate_type_, _variate_tag_>` and is extracted with the `weighted_variate()`
+extractor. For more implementation details, see 
+[classref boost::accumulators::impl::weighted_covariance_impl [^weighted_covariance_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::outer_product<
+                        numeric::functional::multiplies<
+                            _weight_type_
+                          , numeric::functional::average<_sample_type_, std::size_t>::result_type
+                        >::result_type
+                      , numeric::functional::multiplies<
+                            _weight_type_
+                          , numeric::functional::average<_variate_type_, std::size_t>::result_type
+                        >::result_type
+                    >
+                    ``]]
+    [[Depends On] [`count` \n 
+                   `sum_of_weights` \n 
+                   `weighted_mean` \n 
+                   `weighted_mean_of_variates<_variate_type_, _variate_tag_>`]]
+    [[Variants] [`abstract_weighted_covariance`]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [`weight` \n
+                               `_variate_tag_`]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<double, stats<tag::weighted_covariance<double, tag::covariate1> >, double > acc;
+
+    acc(1., weight = 1.1, covariate1 = 2.);
+    acc(1., weight = 2.2, covariate1 = 4.);
+    acc(2., weight = 3.3, covariate1 = 3.);
+    acc(6., weight = 4.4, covariate1 = 1.);        
+
+    double epsilon = 1e-6;
+    BOOST_CHECK_CLOSE(weighted_covariance(acc), -2.39, epsilon);
+
+[*See also]
+
+* [classref boost::accumulators::impl::weighted_covariance_impl [^weighted_covariance_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.sum [^sum]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.weighted_mean [^weighted_mean]]
+
+[endsect]
+
+[section:weighted_density weighted_density]
+
+The `tag::weighted_density` feature returns a histogram of the weighted sample distribution. For more
+implementation details, see [classref boost::accumulators::impl::weighted_density_impl [^weighted_density_impl]].
+
+[variablelist
+    [[Result Type] [``
+                    iterator_range<
+                        std::vector<
+                            std::pair<
+                                numeric::functional::average<_weight_type_, std::size_t>::result_type
+                              , numeric::functional::average<_weight_type_, std::size_t>::result_type
+                            >
+                        >::iterator
+                    >
+                    ``]]
+    [[Depends On] [`count` \n `sum_of_weights` \n `min` \n `max`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [`tag::weighted_density::cache_size` \n `tag::weighted_density::num_bins`]]
+    [[Accumulator Parameters] [`weight`]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [O(N), when N is `weighted_density::num_bins`]] 
+]
+
+[/ TODO add example ]
+
+[*See also]
+
+* [classref boost::accumulators::impl::weighted_density_impl [^weighted_density_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.sum [^sum]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.min [^min]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.max [^max]]
+
+[endsect]
+
+[section:weighted_extended_p_square weighted_extended_p_square]
+
+Multiple quantile estimation with the extended [^P^2] algorithm for weighted samples. For further 
+details, see [classref boost::accumulators::impl::weighted_extended_p_square_impl [^weighted_extended_p_square_impl]].
+
+[variablelist
+    [[Result Type] [``
+                    boost::iterator_range<
+                        _implementation_defined_
+                    >
+                    ``]]
+    [[Depends On] [`count` \n `sum_of_weights`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [`tag::weighted_extended_p_square::probabilities`]]
+    [[Accumulator Parameters] [`weight`]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    typedef accumulator_set<double, stats<tag::weighted_extended_p_square>, double> accumulator_t;
+
+    // tolerance in %
+    double epsilon = 1;
+    
+    // some random number generators
+    double mu1 = -1.0;
+    double mu2 =  1.0;
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma1(mu1, 1);
+    boost::normal_distribution<> mean_sigma2(mu2, 1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal1(rng, mean_sigma1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal2(rng, mean_sigma2);
+    
+    std::vector<double> probs_uniform, probs_normal1, probs_normal2, probs_normal_exact1, probs_normal_exact2;
+    
+    double p1[] = {/*0.001,*/ 0.01, 0.1, 0.5, 0.9, 0.99, 0.999};
+    probs_uniform.assign(p1, p1 + sizeof(p1) / sizeof(double));
+    
+    double p2[] = {0.001, 0.025};
+    double p3[] = {0.975, 0.999};
+    probs_normal1.assign(p2, p2 + sizeof(p2) / sizeof(double));
+    probs_normal2.assign(p3, p3 + sizeof(p3) / sizeof(double));
+    
+    double p4[] = {-3.090232, -1.959963};
+    double p5[] = {1.959963, 3.090232};
+    probs_normal_exact1.assign(p4, p4 + sizeof(p4) / sizeof(double));
+    probs_normal_exact2.assign(p5, p5 + sizeof(p5) / sizeof(double));
+    
+    accumulator_t acc_uniform(tag::weighted_extended_p_square::probabilities = probs_uniform);
+    accumulator_t acc_normal1(tag::weighted_extended_p_square::probabilities = probs_normal1);
+    accumulator_t acc_normal2(tag::weighted_extended_p_square::probabilities = probs_normal2);
+    
+    for (std::size_t i = 0; i < 100000; ++i)
+    {
+        acc_uniform(rng(), weight = 1.);
+        
+        double sample1 = normal1();
+        double sample2 = normal2();
+        acc_normal1(sample1, weight = std::exp(-mu1 * (sample1 - 0.5 * mu1)));
+        acc_normal2(sample2, weight = std::exp(-mu2 * (sample2 - 0.5 * mu2)));
+    }
+    
+    // check for uniform distribution    
+    for (std::size_t i = 0; i < probs_uniform.size(); ++i)
+    {
+        BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_uniform)[i], probs_uniform[i], epsilon);
+    }
+    
+    // check for standard normal distribution
+    for (std::size_t i = 0; i < probs_normal1.size(); ++i)
+    {
+        BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_normal1)[i], probs_normal_exact1[i], epsilon);
+        BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_normal2)[i], probs_normal_exact2[i], epsilon);
+    }
+
+[*See also]
+
+* [classref boost::accumulators::impl::weighted_extended_p_square_impl [^weighted_extended_p_square_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.sum [^sum]]
+
+[endsect]
+
+[section:weighted_kurtosis weighted_kurtosis]
+
+The kurtosis of a sample distribution is defined as the ratio of the 4th central moment and the
+square of the 2nd central moment (the variance) of the samples, minus 3. The term [^-3] is added
+in order to ensure that the normal distribution has zero kurtosis. For more implementation 
+details, see [classref boost::accumulators::impl::weighted_kurtosis_impl [^weighted_kurtosis_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<
+                        numeric::functional::multiplies<_sample_type_, _weight_type_>::result_type
+                      , numeric::functional::multiplies<_sample_type_, _weight_type_>::result_type
+                    >::result_type
+                    ``]]
+    [[Depends On] [`weighted_mean` \n `weighted_moment<2>` \n `weighted_moment<3>` \n `weighted_moment<4>`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<int, stats<tag::weighted_kurtosis>, int > acc2;
+    
+    acc2(2, weight = 4);
+    acc2(7, weight = 1);
+    acc2(4, weight = 3);
+    acc2(9, weight = 1);
+    acc2(3, weight = 2);
+    
+    BOOST_CHECK_EQUAL( weighted_mean(acc2), 42./11. );
+    BOOST_CHECK_EQUAL( weighted_moment<2>(acc2), 212./11. );
+    BOOST_CHECK_EQUAL( weighted_moment<3>(acc2), 1350./11. );
+    BOOST_CHECK_EQUAL( weighted_moment<4>(acc2), 9956./11. );
+    BOOST_CHECK_CLOSE( weighted_kurtosis(acc2), 0.58137026432, 1e-6 );
+
+[*See also]
+
+* [classref boost::accumulators::impl::weighted_kurtosis_impl [^weighted_kurtosis_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.weighted_mean [^weighted_mean]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.weighted_moment [^weighted_moment]]
+
+[endsect]
+
+[section:weighted_mean weighted_mean ['and variants]]
+
+Calculates the weighted mean of samples or variates. The calculation is either
+lazy (in the result extractor), or immediate (in the accumulator). The lazy implementation
+is the default. For more implementation details, see 
+[classref boost::accumulators::impl::weighted_mean_impl [^weighted_mean_impl]] or.
+[classref boost::accumulators::impl::immediate_weighted_mean_impl [^immediate_weighted_mean_impl]]
+
+[variablelist
+    [[Result Type] [For samples, `numeric::functional::average<numeric::functional::multiplies<_sample_type_, _weight_type_>::result_type, _weight_type_>::result_type` \n
+                    For variates, `numeric::functional::average<numeric::functional::multiplies<_variate_type_, _weight_type_>::result_type, _weight_type_>::result_type`]]
+    [[Depends On] [`sum_of_weights` \n
+                   The lazy mean of samples depends on `weighted_sum` \n
+                   The lazy mean of variates depends on `weighted_sum_of_variates<>`]]
+    [[Variants] [`weighted_mean_of_variates<_variate_type_, _variate_tag_>` \n
+                 `immediate_weighted_mean` \n
+                 `immediate_weighted_mean_of_variates<_variate_type_, _variate_tag_>`]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [['none]]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<
+        int
+      , stats<
+            tag::weighted_mean
+          , tag::weighted_mean_of_variates<int, tag::covariate1>
+        >
+      , int
+    > acc;
+
+    acc(10, weight = 2, covariate1 = 7);          //  20
+    BOOST_CHECK_EQUAL(2, sum_of_weights(acc));    //
+                                                  //
+    acc(6, weight = 3, covariate1 = 8);           //  18
+    BOOST_CHECK_EQUAL(5, sum_of_weights(acc));    //
+                                                  //
+    acc(4, weight = 4, covariate1 = 9);           //  16
+    BOOST_CHECK_EQUAL(9, sum_of_weights(acc));    //
+                                                  //
+    acc(6, weight = 5, covariate1 = 6);           //+ 30
+    BOOST_CHECK_EQUAL(14, sum_of_weights(acc));   //
+                                                  //= 84  / 14 = 6
+
+    BOOST_CHECK_EQUAL(6., weighted_mean(acc));
+    BOOST_CHECK_EQUAL(52./7., (weighted_mean_of_variates<int, tag::covariate1>(acc)));
+
+    accumulator_set<
+        int
+      , stats<
+            tag::weighted_mean(immediate)
+          , tag::weighted_mean_of_variates<int, tag::covariate1>(immediate)
+        >
+      , int
+    > acc2;
+
+    acc2(10, weight = 2, covariate1 = 7);         //  20
+    BOOST_CHECK_EQUAL(2, sum_of_weights(acc2));   //
+                                                  //
+    acc2(6, weight = 3, covariate1 = 8);          //  18
+    BOOST_CHECK_EQUAL(5, sum_of_weights(acc2));   //
+                                                  //
+    acc2(4, weight = 4, covariate1 = 9);          //  16
+    BOOST_CHECK_EQUAL(9, sum_of_weights(acc2));   //
+                                                  //
+    acc2(6, weight = 5, covariate1 = 6);          //+ 30
+    BOOST_CHECK_EQUAL(14, sum_of_weights(acc2));  //
+                                                  //= 84  / 14 = 6
+
+    BOOST_CHECK_EQUAL(6., weighted_mean(acc2));
+    BOOST_CHECK_EQUAL(52./7., (weighted_mean_of_variates<int, tag::covariate1>(acc2)));
+
+[*See also]
+
+* [classref boost::accumulators::impl::weighted_mean_impl [^weighted_mean_impl]]
+* [classref boost::accumulators::impl::immediate_weighted_mean_impl [^immediate_weighted_mean_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.weighted_sum [^weighted_sum]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.sum [^sum]]
+
+[endsect]
+
+[section:weighted_median weighted_median ['and variants]]
+
+Median estimation for weighted samples based on the [^P^2] quantile estimator, the density estimator, or
+the [^P^2] cumulative distribution estimator. For more implementation details, see
+[classref boost::accumulators::impl::weighted_median_impl [^weighted_median_impl]], 
+[classref boost::accumulators::impl::with_weighted_density_median_impl [^with_weighted_density_median_impl]], 
+and [classref boost::accumulators::impl::with_weighted_p_square_cumulative_distribution_median_impl [^with_weighted_p_square_cumulative_distribution_median_impl]].
+
+The three median accumulators all satisfy the `tag::weighted_median` feature, and can all be
+extracted with the `weighted_median()` extractor.
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<_sample_type_, std::size_t>::result_type
+                    ``]]
+    [[Depends On] [`weighted_median` depends on `weighted_p_square_quantile_for_median` \n
+                   `with_weighted_density_median` depends on `count` and `weighted_density` \n
+                   `with_weighted_p_square_cumulative_distribution_median` depends on `weighted_p_square_cumulative_distribution`]]
+    [[Variants] [`with_weighted_density_median` (a.k.a. `weighted_median(with_weighted_density)`) \n
+                 `with_weighted_p_square_cumulative_distribution_median` (a.k.a. `weighted_median(with_weighted_p_square_cumulative_distribution)`)]]
+    [[Initialization Parameters] [`with_weighted_density_median` requires `tag::weighted_density::cache_size` and `tag::weighted_density::num_bins` \n
+                                  `with_weighted_p_square_cumulative_distribution_median` requires `tag::weighted_p_square_cumulative_distribution::num_cells`]]
+    [[Accumulator Parameters] [`weight`]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [TODO]] 
+]
+
+[*Example]
+
+    // Median estimation of normal distribution N(1,1) using samples from a narrow normal distribution N(1,0.01)
+    // The weights equal to the likelihood ratio of the corresponding samples
+    
+    // two random number generators
+    double mu = 1.;
+    double sigma_narrow = 0.01;
+    double sigma = 1.;
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma_narrow(mu,sigma_narrow);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal_narrow(rng, mean_sigma_narrow);
+    
+    accumulator_set<double, stats<tag::weighted_median(with_weighted_p_square_quantile) >, double > acc;
+    accumulator_set<double, stats<tag::weighted_median(with_weighted_density) >, double > 
+        acc_dens( tag::weighted_density::cache_size = 10000, tag::weighted_density::num_bins = 1000 );
+    accumulator_set<double, stats<tag::weighted_median(with_weighted_p_square_cumulative_distribution) >, double > 
+        acc_cdist( tag::weighted_p_square_cumulative_distribution::num_cells = 100 );
+        
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        double sample = normal_narrow();
+        acc(sample, weight = std::exp(0.5 * (sample - mu) * (sample - mu) * ( 1./sigma_narrow/sigma_narrow - 1./sigma/sigma )));
+        acc_dens(sample, weight = std::exp(0.5 * (sample - mu) * (sample - mu) * ( 1./sigma_narrow/sigma_narrow - 1./sigma/sigma )));
+        acc_cdist(sample, weight = std::exp(0.5 * (sample - mu) * (sample - mu) * ( 1./sigma_narrow/sigma_narrow - 1./sigma/sigma )));
+    }
+    
+    BOOST_CHECK_CLOSE(1., weighted_median(acc), 1e-1);
+    BOOST_CHECK_CLOSE(1., weighted_median(acc_dens), 1e-1);
+    BOOST_CHECK_CLOSE(1., weighted_median(acc_cdist), 1e-1);
+
+[*See also]
+
+* [classref boost::accumulators::impl::weighted_median_impl [^weighted_median_impl]]
+* [classref boost::accumulators::impl::with_weighted_density_median_impl [^with_weighted_density_median_impl]]
+* [classref boost::accumulators::impl::with_weighted_p_square_cumulative_distribution_median_impl [^with_weighted_p_square_cumulative_distribution_median_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.weighted_p_square_quantile [^weighted_p_square_quantile]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.weighted_p_square_cumulative_distribution [^weighted_p_square_cumulative_distribution]]
+
+[endsect]
+
+[section:weighted_moment weighted_moment]
+
+Calculates the N-th moment of the weighted samples, which is defined as the sum of the weighted N-th
+power of the samples over the sum of the weights.
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<
+                        numeric::functional::multiplies<_sample_type_, _weight_type_>::result_type
+                      , weight_type
+                    >::result_type
+                    ``]]
+    [[Depends On] [`count` \n `sum_of_weights`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [`weight`]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<double, stats<tag::weighted_moment<2> >, double> acc2;
+    accumulator_set<double, stats<tag::weighted_moment<7> >, double> acc7;
+    
+    acc2(2.1, weight = 0.7);
+    acc2(2.7, weight = 1.4);
+    acc2(1.8, weight = 0.9);
+    
+    acc7(2.1, weight = 0.7);
+    acc7(2.7, weight = 1.4);
+    acc7(1.8, weight = 0.9);
+    
+    BOOST_CHECK_CLOSE(5.403, weighted_moment<2>(acc2), 1e-5);
+    BOOST_CHECK_CLOSE(548.54182, weighted_moment<7>(acc7), 1e-5);
+
+[*See also]
+
+* [classref boost::accumulators::impl::weighted_moment_impl [^weighted_moment_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.sum [^sum]]
+
+[endsect]
+
+[section:weighted_p_square_cumulative_distribution weighted_p_square_cumulative_distribution]
+
+Histogram calculation of the cumulative distribution with the [^P^2] algorithm for weighted samples.
+For more implementation details, see 
+[classref boost::accumulators::impl::weighted_p_square_cumulative_distribution_impl [^weighted_p_square_cumulative_distribution_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    iterator_range<
+                        std::vector<
+                            std::pair<
+                                numeric::functional::average<weighted_sample, std::size_t>::result_type
+                              , numeric::functional::average<weighted_sample, std::size_t>::result_type
+                            >
+                        >::iterator
+                    >
+                    ``
+                    where `weighted_sample` is `numeric::functional::multiplies<_sample_type_, _weight_type_>::result_type`]]
+    [[Depends On] [`count` \n `sum_or_weights`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [`tag::weighted_p_square_cumulative_distribution::num_cells`]]
+    [[Accumulator Parameters] [`weight`]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [O(N) where N is `num_cells`]] 
+]
+
+[*Example]
+
+    // tolerance in %
+    double epsilon = 4;
+
+    typedef accumulator_set<double, stats<tag::weighted_p_square_cumulative_distribution>, double > accumulator_t;
+        
+    accumulator_t acc_upper(tag::weighted_p_square_cumulative_distribution::num_cells = 100);
+    accumulator_t acc_lower(tag::weighted_p_square_cumulative_distribution::num_cells = 100);
+    
+    // two random number generators
+    double mu_upper = 1.0;
+    double mu_lower = -1.0;
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma_upper(mu_upper,1);
+    boost::normal_distribution<> mean_sigma_lower(mu_lower,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal_upper(rng, mean_sigma_upper);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal_lower(rng, mean_sigma_lower);
+    
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        double sample = normal_upper();
+        acc_upper(sample, weight = std::exp(-mu_upper * (sample - 0.5 * mu_upper)));
+    }
+    
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        double sample = normal_lower();
+        acc_lower(sample, weight = std::exp(-mu_lower * (sample - 0.5 * mu_lower)));
+    }
+    
+    typedef iterator_range<std::vector<std::pair<double, double> >::iterator > histogram_type;
+    histogram_type histogram_upper = weighted_p_square_cumulative_distribution(acc_upper);
+    histogram_type histogram_lower = weighted_p_square_cumulative_distribution(acc_lower);
+    
+    // Note that applaying importance sampling results in a region of the distribution 
+    // to be estimated more accurately and another region to be estimated less accurately
+    // than without importance sampling, i.e., with unweighted samples
+    
+    for (std::size_t i = 0; i < histogram_upper.size(); ++i)
+    {   
+        // problem with small results: epsilon is relative (in percent), not absolute!
+        
+        // check upper region of distribution
+        if ( histogram_upper[i].second > 0.1 )    
+            BOOST_CHECK_CLOSE( 0.5 * (1.0 + erf( histogram_upper[i].first / sqrt(2.0) )), histogram_upper[i].second, epsilon );
+        // check lower region of distribution
+        if ( histogram_lower[i].second < -0.1 )    
+            BOOST_CHECK_CLOSE( 0.5 * (1.0 + erf( histogram_lower[i].first / sqrt(2.0) )), histogram_lower[i].second, epsilon );
+    }        
+
+[*See also]
+
+* [classref boost::accumulators::impl::weighted_p_square_cumulative_distribution_impl [^weighted_p_square_cumulative_distribution_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.sum [^sum]]
+
+[endsect]
+
+[section:weighted_p_square_quantile weighted_p_square_quantile ['and variants]]
+
+Single quantile estimation with the [^P^2] algorithm. For more implementation details, see
+[classref boost::accumulators::impl::weighted_p_square_quantile_impl [^weighted_p_square_quantile_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<
+                        numeric::functional::multiplies<_sample_type_, _weight_type_>::result_type
+                      , std::size_t
+                    >::result_type
+                    ``]]
+    [[Depends On] [`count` \n `sum_of_weights`]]
+    [[Variants] [`weighted_p_square_quantile_for_median`]]
+    [[Initialization Parameters] [`quantile_probability`, which defaults to `0.5`.
+                                  (Note: for `weighted_p_square_quantile_for_median`, the `quantile_probability`
+                                  parameter is ignored and is always `0.5`.)]]
+    [[Accumulator Parameters] [`weight`]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [TODO]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    typedef accumulator_set<double, stats<tag::weighted_p_square_quantile>, double> accumulator_t;
+
+    // tolerance in %
+    double epsilon = 1;
+    
+    // some random number generators
+    double mu4 = -1.0;
+    double mu5 = -1.0;
+    double mu6 = 1.0;
+    double mu7 = 1.0;
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma4(mu4, 1);
+    boost::normal_distribution<> mean_sigma5(mu5, 1);
+    boost::normal_distribution<> mean_sigma6(mu6, 1);
+    boost::normal_distribution<> mean_sigma7(mu7, 1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal4(rng, mean_sigma4);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal5(rng, mean_sigma5);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal6(rng, mean_sigma6);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal7(rng, mean_sigma7);
+        
+    accumulator_t acc0(quantile_probability = 0.001);
+    accumulator_t acc1(quantile_probability = 0.025);
+    accumulator_t acc2(quantile_probability = 0.975);
+    accumulator_t acc3(quantile_probability = 0.999);
+
+    accumulator_t acc4(quantile_probability = 0.001);
+    accumulator_t acc5(quantile_probability = 0.025);
+    accumulator_t acc6(quantile_probability = 0.975);
+    accumulator_t acc7(quantile_probability = 0.999);
+
+        
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        double sample = rng();
+        acc0(sample, weight = 1.);
+        acc1(sample, weight = 1.);
+        acc2(sample, weight = 1.);
+        acc3(sample, weight = 1.);
+        
+        double sample4 = normal4();
+        double sample5 = normal5();
+        double sample6 = normal6();
+        double sample7 = normal7();
+        acc4(sample4, weight = std::exp(-mu4 * (sample4 - 0.5 * mu4)));
+        acc5(sample5, weight = std::exp(-mu5 * (sample5 - 0.5 * mu5)));
+        acc6(sample6, weight = std::exp(-mu6 * (sample6 - 0.5 * mu6)));
+        acc7(sample7, weight = std::exp(-mu7 * (sample7 - 0.5 * mu7)));
+    }
+    
+    // check for uniform distribution with weight = 1
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc0), 0.001, 15 );
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc1), 0.025, 5 );
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc2), 0.975, epsilon );
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc3), 0.999, epsilon );
+    
+    // check for shifted standard normal distribution ("importance sampling")
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc4), -3.090232, epsilon );
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc5), -1.959963, epsilon );
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc6),  1.959963, epsilon );
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc7),  3.090232, epsilon );
+
+[*See also]
+
+* [classref boost::accumulators::impl::weighted_p_square_quantile_impl [^weighted_p_square_quantile_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.sum [^sum]]
+
+[endsect]
+
+[section:weighted_skewness weighted_skewness]
+
+The skewness of a sample distribution is defined as the ratio of the 3rd central moment and the [^3/2]-th power 
+of the 2nd central moment (the variance) of the sampless 3. The skewness estimator for weighted samples 
+is formally identical to the estimator for unweighted samples, except that the weighted counterparts of
+all measures it depends on are to be taken.
+
+For implementation details, see
+[classref boost::accumulators::impl::weighted_skewness_impl [^weighted_skewness_impl]].
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<
+                        numeric::functional::multiplies<_sample_type_, _weight_type_>::result_type
+                      , numeric::functional::multiplies<_sample_type_, _weight_type_>::result_type
+                    >::result_type
+                    ``]]
+    [[Depends On] [`weighted_mean` \n `weighted_moment<2>` \n `weighted_moment<3>`]]
+    [[Variants] [['none]]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [`weight`]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<int, stats<tag::weighted_skewness>, int > acc2;
+    
+    acc2(2, weight = 4);
+    acc2(7, weight = 1);
+    acc2(4, weight = 3);
+    acc2(9, weight = 1);
+    acc2(3, weight = 2);
+    
+    BOOST_CHECK_EQUAL( weighted_mean(acc2), 42./11. );
+    BOOST_CHECK_EQUAL( weighted_moment<2>(acc2), 212./11. );
+    BOOST_CHECK_EQUAL( weighted_moment<3>(acc2), 1350./11. );
+    BOOST_CHECK_CLOSE( weighted_skewness(acc2), 1.30708406282, 1e-6 );
+
+[*See also]
+
+* [classref boost::accumulators::impl::weighted_skewness_impl [^weighted_skewness_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.weighted_mean [^weighted_mean]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.weighted_moment [^weighted_moment]]
+
+[endsect]
+
+[section:weighted_sum weighted_sum ['and variants]]
+
+For summing the weighted samples or variates. All of the `tag::weighted_sum_of_variates<>` features 
+can be extracted with the `weighted_sum_of_variates()` extractor.
+
+[variablelist
+    [[Result Type] [`numeric::functional::multiplies<_sample_type_, _weight_type_>::result_type` for summing weighted samples \n
+                    `numeric::functional::multiplies<_variate_type_, _weight_type_>::result_type` for summing weighted variates]]
+    [[Depends On] [['none]]]
+    [[Variants] [`tag::weighted_sum` \n
+                 `tag::weighted_sum_of_variates<_variate_type_, _variate_tag_>`]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [`weight` \n
+                               `_variate_tag_` for summing variates]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    accumulator_set<int, stats<tag::weighted_sum, tag::weighted_sum_of_variates<int, tag::covariate1> >, int> acc;
+
+    acc(1, weight = 2, covariate1 = 3);
+    BOOST_CHECK_EQUAL(2, weighted_sum(acc));
+    BOOST_CHECK_EQUAL(6, weighted_sum_of_variates(acc));
+
+    acc(2, weight = 3, covariate1 = 6);
+    BOOST_CHECK_EQUAL(8, weighted_sum(acc));
+    BOOST_CHECK_EQUAL(24, weighted_sum_of_variates(acc));
+
+    acc(4, weight = 6, covariate1 = 9);
+    BOOST_CHECK_EQUAL(32, weighted_sum(acc));
+    BOOST_CHECK_EQUAL(78, weighted_sum_of_variates(acc));
+
+[*See also]
+
+* [classref boost::accumulators::impl::weighted_sum_impl [^weighted_sum_impl]]
+
+[endsect]
+
+[section:weighted_variance weighted_variance ['and variants]]
+
+Lazy or iterative calculation of the weighted variance. The lazy calculation is associated with the `tag::weighted_variance`
+feature, and the iterative calculation with the `tag::immediate_weighted_variance` feature. Both can be extracted
+using the `tag::weighted_variance()` extractor. For more implementation details, see
+[classref boost::accumulators::impl::weighted_variance_impl [^weighted_variance_impl]] and
+[classref boost::accumulators::impl::immediate_weighted_variance_impl [^immediate_weighted_variance_impl]]
+
+[variablelist
+    [[Result Type] [``
+                    numeric::functional::average<
+                        numeric::functional::multiplies<_sample_type_, _weight_type_>::result_type
+                      , std::size_t
+                    >::result_type
+                    ``]]
+    [[Depends On] [`tag::weighted_variance` depends on `tag::weighted_moment<2>` and `tag::weighted_mean` \n
+                   `tag::immediate_weighted_variance` depends on `tag::count` and `tag::immediate_weighted_mean`]]
+    [[Variants] [`tag::weighted_variance` (a.k.a. `tag::weighted_variance(lazy))` \n
+                 `tag::immediate_weighted_variance` (a.k.a. `tag::weighted_variance(immediate)`)]]
+    [[Initialization Parameters] [['none]]]
+    [[Accumulator Parameters] [`weight`]]
+    [[Extractor Parameters] [['none]]]
+    [[Accumulator Complexity] [O(1)]] 
+    [[Extractor Complexity] [O(1)]] 
+]
+
+[*Example]
+
+    // basic lazy weighted_variance
+    accumulator_set<int, stats<tag::weighted_variance>, int> acc1;
+
+    acc1(1, weight = 2);    //  2
+    acc1(2, weight = 3);    //  6
+    acc1(3, weight = 1);    //  3
+    acc1(4, weight = 4);    // 16
+    acc1(5, weight = 1);    //  5
+
+    // weighted_mean = (2+6+3+16+5) / (2+3+1+4+1) = 32 / 11 = 2.9090909090909090909090909090909
+
+    BOOST_CHECK_EQUAL(5u, count(acc1));
+    BOOST_CHECK_CLOSE(2.9090909, weighted_mean(acc1), 1e-5);
+    BOOST_CHECK_CLOSE(10.1818182, weighted_moment<2>(acc1), 1e-5);
+    BOOST_CHECK_CLOSE(1.7190083, weighted_variance(acc1), 1e-5);
+
+    accumulator_set<int, stats<tag::weighted_variance(immediate)>, int> acc2;
+
+    acc2(1, weight = 2);
+    acc2(2, weight = 3);
+    acc2(3, weight = 1);
+    acc2(4, weight = 4);
+    acc2(5, weight = 1);
+
+    BOOST_CHECK_EQUAL(5u, count(acc2));
+    BOOST_CHECK_CLOSE(2.9090909, weighted_mean(acc2), 1e-5);
+    BOOST_CHECK_CLOSE(1.7190083, weighted_variance(acc2), 1e-5);
+    
+    // check lazy and immediate variance with random numbers
+    
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(0,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+    
+    accumulator_set<double, stats<tag::weighted_variance>, double > acc_lazy;    
+    accumulator_set<double, stats<tag::weighted_variance(immediate)>, double > acc_immediate;
+    
+    for (std::size_t i=0; i<10000; ++i)
+    {
+        double value = normal();
+        acc_lazy(value, weight = rng());
+        acc_immediate(value, weight = rng());
+    }
+    
+    BOOST_CHECK_CLOSE(1., weighted_variance(acc_lazy), 1.);
+    BOOST_CHECK_CLOSE(1., weighted_variance(acc_immediate), 1.);
+
+[*See also]
+
+* [classref boost::accumulators::impl::weighted_variance_impl [^weighted_variance_impl]]
+* [classref boost::accumulators::impl::immediate_weighted_variance_impl [^immediate_weighted_variance_impl]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.count [^count]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.weighted_mean [^weighted_mean]]
+* [link accumulators.user_s_guide.the_statistical_accumulators_library.weighted_moment [^weighted_moment]]
+
+[endsect]
+
+[endsect]
+
+[endsect]
+
+[section Acknowledgements]
+
+Boost.Accumulators represents the efforts of many individuals. I would like to thank 
+Daniel Egloff of _ZKB_ for helping to conceive the library and realize its 
+implementation. I would also like to thank David Abrahams and Matthias Troyer for 
+their key contributions to the design of the library. Many thanks are due to Michael 
+Gauckler and Olivier Gygi, who, along with Daniel Egloff, implemented many of the 
+statistical accumulators.
+
+Finally, I would like to thank _ZKB_ for sponsoring the work on Boost.Accumulators 
+and graciously donating it to the community. 
+
+[endsect]
+
+[section Reference]
+
+[xinclude accdoc.xml]
+
+[xinclude statsdoc.xml]
+
+[xinclude opdoc.xml]
+
+[endsect]

Added: trunk/libs/accumulators/example/Jamfile.v2
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/example/Jamfile.v2	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,11 @@
+# (C) Copyright 2004: Eric Niebler
+# Distributed under the Boost Software License, Version 1.0.
+# (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+exe example
+    :
+        main.cpp
+    :
+        <include>../../..
+        <include>$(BOOST_ROOT)
+    ;

Added: trunk/libs/accumulators/example/example.vcproj
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/example/example.vcproj	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,388 @@
+<?xml version="1.0" encoding="Windows-1252"?>
+<VisualStudioProject
+	ProjectType="Visual C++"
+	Version="7.10"
+	Name="example"
+	ProjectGUID="{57D2AB8B-8CBB-4B28-921E-C6916109B843}"
+	Keyword="Win32Proj">
+	<Platforms>
+		<Platform
+			Name="Win32"/>
+	</Platforms>
+	<Configurations>
+		<Configuration
+			Name="Debug|Win32"
+			OutputDirectory="Debug"
+			IntermediateDirectory="Debug"
+			ConfigurationType="1"
+			CharacterSet="2">
+			<Tool
+				Name="VCCLCompilerTool"
+				Optimization="0"
+				AdditionalIncludeDirectories="..\..\..;$(BOOST_ROOT)"
+				PreprocessorDefinitions="WIN32;_DEBUG;_CONSOLE"
+				MinimalRebuild="TRUE"
+				BasicRuntimeChecks="3"
+				RuntimeLibrary="5"
+				UsePrecompiledHeader="0"
+				WarningLevel="3"
+				Detect64BitPortabilityProblems="TRUE"
+				DebugInformationFormat="3"/>
+			<Tool
+				Name="VCCustomBuildTool"/>
+			<Tool
+				Name="VCLinkerTool"
+				OutputFile="$(OutDir)/example.exe"
+				LinkIncremental="2"
+				GenerateDebugInformation="TRUE"
+				ProgramDatabaseFile="$(OutDir)/example.pdb"
+				SubSystem="1"
+				TargetMachine="1"/>
+			<Tool
+				Name="VCMIDLTool"/>
+			<Tool
+				Name="VCPostBuildEventTool"/>
+			<Tool
+				Name="VCPreBuildEventTool"/>
+			<Tool
+				Name="VCPreLinkEventTool"/>
+			<Tool
+				Name="VCResourceCompilerTool"/>
+			<Tool
+				Name="VCWebServiceProxyGeneratorTool"/>
+			<Tool
+				Name="VCXMLDataGeneratorTool"/>
+			<Tool
+				Name="VCWebDeploymentTool"/>
+			<Tool
+				Name="VCManagedWrapperGeneratorTool"/>
+			<Tool
+				Name="VCAuxiliaryManagedWrapperGeneratorTool"/>
+		</Configuration>
+		<Configuration
+			Name="Release|Win32"
+			OutputDirectory="Release"
+			IntermediateDirectory="Release"
+			ConfigurationType="1"
+			CharacterSet="2">
+			<Tool
+				Name="VCCLCompilerTool"
+				AdditionalIncludeDirectories="..\..\..;$(BOOST_ROOT)"
+				PreprocessorDefinitions="WIN32;NDEBUG;_CONSOLE"
+				RuntimeLibrary="4"
+				UsePrecompiledHeader="0"
+				WarningLevel="3"
+				Detect64BitPortabilityProblems="TRUE"
+				DebugInformationFormat="3"/>
+			<Tool
+				Name="VCCustomBuildTool"/>
+			<Tool
+				Name="VCLinkerTool"
+				OutputFile="$(OutDir)/example.exe"
+				LinkIncremental="1"
+				GenerateDebugInformation="TRUE"
+				SubSystem="1"
+				OptimizeReferences="2"
+				EnableCOMDATFolding="2"
+				TargetMachine="1"/>
+			<Tool
+				Name="VCMIDLTool"/>
+			<Tool
+				Name="VCPostBuildEventTool"/>
+			<Tool
+				Name="VCPreBuildEventTool"/>
+			<Tool
+				Name="VCPreLinkEventTool"/>
+			<Tool
+				Name="VCResourceCompilerTool"/>
+			<Tool
+				Name="VCWebServiceProxyGeneratorTool"/>
+			<Tool
+				Name="VCXMLDataGeneratorTool"/>
+			<Tool
+				Name="VCWebDeploymentTool"/>
+			<Tool
+				Name="VCManagedWrapperGeneratorTool"/>
+			<Tool
+				Name="VCAuxiliaryManagedWrapperGeneratorTool"/>
+		</Configuration>
+	</Configurations>
+	<References>
+	</References>
+	<Files>
+		<Filter
+			Name="Source Files"
+			Filter="cpp;c;cxx;def;odl;idl;hpj;bat;asm;asmx"
+			UniqueIdentifier="{4FC737F1-C7A5-4376-A066-2A32D752A2FF}">
+			<File
+				RelativePath=".\main.cpp">
+			</File>
+		</Filter>
+		<Filter
+			Name="Header Files"
+			Filter="h;hpp;hxx;hm;inl;inc;xsd"
+			UniqueIdentifier="{93995380-89BD-4b04-88EB-625FBE52EBFB}">
+			<File
+				RelativePath="..\..\..\boost\accumulators\accumulators.hpp">
+			</File>
+			<File
+				RelativePath="..\..\..\boost\accumulators\accumulators_fwd.hpp">
+			</File>
+			<File
+				RelativePath="..\..\..\boost\accumulators\statistics.hpp">
+			</File>
+			<File
+				RelativePath="..\..\..\boost\accumulators\statistics_fwd.hpp">
+			</File>
+			<Filter
+				Name="statistics"
+				Filter="">
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\count.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\covariance.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\density.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\error_of.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\error_of_mean.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\extended_p_square.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\extended_p_square_quantile.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\kurtosis.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\max.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\mean.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\median.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\min.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\moment.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\p_square_cumulative_distribution.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\p_square_quantile.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\peaks_over_threshold.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\pot_quantile.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\pot_tail_mean.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\skewness.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\stats.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\sum.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\tail.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\tail_mean.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\tail_quantile.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\tail_variate.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\tail_variate_means.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\times2_iterator.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\variance.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\weighted_covariance.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\weighted_density.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\weighted_extended_p_square.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\weighted_kurtosis.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\weighted_mean.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\weighted_median.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\weighted_moment.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\weighted_p_square_cumulative_distribution.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\weighted_p_square_quantile.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\weighted_skewness.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\weighted_sum.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\weighted_variance.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\statistics\with_error.hpp">
+				</File>
+				<Filter
+					Name="variates"
+					Filter="">
+					<File
+						RelativePath="..\..\..\boost\accumulators\statistics\variates\covariate.hpp">
+					</File>
+				</Filter>
+				<Filter
+					Name="parameters"
+					Filter="">
+					<File
+						RelativePath="..\..\..\boost\accumulators\statistics\parameters\quantile_probability.hpp">
+					</File>
+				</Filter>
+			</Filter>
+			<Filter
+				Name="framework"
+				Filter="">
+				<File
+					RelativePath="..\..\..\boost\accumulators\framework\accumulator_base.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\framework\accumulator_concept.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\framework\accumulator_set.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\framework\depends_on.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\framework\external.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\framework\extractor.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\accumulators\framework\features.hpp">
+				</File>
+				<Filter
+					Name="parameters"
+					Filter="">
+					<File
+						RelativePath="..\..\..\boost\accumulators\framework\parameters\accumulator.hpp">
+					</File>
+					<File
+						RelativePath="..\..\..\boost\accumulators\framework\parameters\sample.hpp">
+					</File>
+					<File
+						RelativePath="..\..\..\boost\accumulators\framework\parameters\weight.hpp">
+					</File>
+					<File
+						RelativePath="..\..\..\boost\accumulators\framework\parameters\weights.hpp">
+					</File>
+				</Filter>
+				<Filter
+					Name="accumulators"
+					Filter="">
+					<File
+						RelativePath="..\..\..\boost\accumulators\framework\accumulators\droppable_accumulator.hpp">
+					</File>
+					<File
+						RelativePath="..\..\..\boost\accumulators\framework\accumulators\external_accumulator.hpp">
+					</File>
+					<File
+						RelativePath="..\..\..\boost\accumulators\framework\accumulators\reference_accumulator.hpp">
+					</File>
+					<File
+						RelativePath="..\..\..\boost\accumulators\framework\accumulators\value_accumulator.hpp">
+					</File>
+				</Filter>
+			</Filter>
+		</Filter>
+		<Filter
+			Name="External Files"
+			Filter="">
+			<Filter
+				Name="detail"
+				Filter="">
+				<File
+					RelativePath="..\..\..\boost\detail\function1.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\detail\function2.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\detail\function3.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\detail\function4.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\detail\function_n.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\detail\pod_singleton.hpp">
+				</File>
+			</Filter>
+			<Filter
+				Name="numeric"
+				Filter="">
+				<File
+					RelativePath="..\..\..\boost\numeric\functional.hpp">
+				</File>
+				<File
+					RelativePath="..\..\..\boost\numeric\functional_fwd.hpp">
+				</File>
+				<Filter
+					Name="functional"
+					Filter="">
+					<File
+						RelativePath="..\..\..\boost\numeric\functional\complex.hpp">
+					</File>
+					<File
+						RelativePath="..\..\..\boost\numeric\functional\valarray.hpp">
+					</File>
+					<File
+						RelativePath="..\..\..\boost\numeric\functional\vector.hpp">
+					</File>
+				</Filter>
+			</Filter>
+		</Filter>
+	</Files>
+	<Globals>
+	</Globals>
+</VisualStudioProject>

Added: trunk/libs/accumulators/example/main.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/example/main.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,169 @@
+///////////////////////////////////////////////////////////////////////////////
+// main.hpp
+//
+//  Copyright 2005 Eric Niebler. Distributed under the Boost
+//  Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <algorithm>
+#include <boost/array.hpp>
+#include <boost/foreach.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics.hpp>
+
+using namespace boost;
+using namespace boost::accumulators;
+
+// Helper that uses BOOST_FOREACH to display a range of doubles
+template<typename Range>
+void output_range(Range const &rng)
+{
+    bool first = true;
+    BOOST_FOREACH(double d, rng)
+    {
+        if(!first) std::cout << ", ";
+        std::cout << d;
+        first = false;
+    }
+    std::cout << '\n';
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// example1
+//
+//  Calculate some useful stats using accumulator_set<> and std::for_each()
+//
+void example1()
+{
+    accumulator_set<
+        double
+      , stats<tag::min, tag::mean(immediate), tag::sum, tag::moment<2> >
+    > acc;
+
+    boost::array<double, 4> data = {0., 1., -1., 3.14159};
+
+    // std::for_each pushes each sample into the accumulator one at a
+    // time, and returns a copy of the accumulator.
+    acc = std::for_each(data.begin(), data.end(), acc);
+
+    std::cout << "  min(acc)        = " << (min)(acc) << std::endl;
+    std::cout << "  mean(acc)       = " << mean(acc) << std::endl;
+
+    // since mean depends on count and sum, we can get their results, too.
+    std::cout << "  count(acc)      = " << count(acc) << std::endl;
+    std::cout << "  sum(acc)        = " << sum(acc) << std::endl;
+    std::cout << "  moment<2>(acc)  = " << moment<2>(acc) << std::endl;
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// example2
+//
+//  Calculate some tail statistics. This demonstrates how to specify 
+//  constructor and accumulator parameters. Note that the tail statistics
+//  return multiple values, which are returned in an iterator_range.
+//
+//  It pushes data in and displays the intermediate results to demonstrate
+//  how the tail statistics are updated.
+void example2()
+{
+    // An accumulator which tracks the right tail (largest N items) and
+    // some data that are covariate with them. N == 4.
+    accumulator_set<
+        double
+      , stats<tag::tail_variate<double, tag::covariate1, right> >
+    > acc(tag::tail<right>::cache_size = 4);
+
+    acc(2.1, covariate1 = .21);
+    acc(1.1, covariate1 = .11);
+    acc(2.1, covariate1 = .21);
+    acc(1.1, covariate1 = .11);
+
+    std::cout << "  tail            = "; output_range(tail(acc));
+    std::cout << "  tail_variate    = "; output_range(tail_variate(acc));
+    std::cout << std::endl;
+
+    acc(21.1, covariate1 = 2.11);
+    acc(11.1, covariate1 = 1.11);
+    acc(21.1, covariate1 = 2.11);
+    acc(11.1, covariate1 = 1.11);
+
+    std::cout << "  tail            = "; output_range(tail(acc));
+    std::cout << "  tail_variate    = "; output_range(tail_variate(acc));
+    std::cout << std::endl;
+
+    acc(42.1, covariate1 = 4.21);
+    acc(41.1, covariate1 = 4.11);
+    acc(42.1, covariate1 = 4.21);
+    acc(41.1, covariate1 = 4.11);
+
+    std::cout << "  tail            = "; output_range(tail(acc));
+    std::cout << "  tail_variate    = "; output_range(tail_variate(acc));
+    std::cout << std::endl;
+
+    acc(32.1, covariate1 = 3.21);
+    acc(31.1, covariate1 = 3.11);
+    acc(32.1, covariate1 = 3.21);
+    acc(31.1, covariate1 = 3.11);
+
+    std::cout << "  tail            = "; output_range(tail(acc));
+    std::cout << "  tail_variate    = "; output_range(tail_variate(acc));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// example3
+//
+//  Demonstrate how to calculate weighted statistics. This example demonstrates
+//  both a simple weighted statistical calculation, and a more complicated
+//  calculation where the weight statistics are calculated and stored in an
+//  external weight accumulataor.
+void example3()
+{
+    // weight == double
+    double w = 1.;
+
+    // Simple weighted calculation
+    {
+        // stats that depend on the weight are made external
+        accumulator_set<double, stats<tag::mean>, double> acc;
+
+        acc(0., weight = w);
+        acc(1., weight = w);
+        acc(-1., weight = w);
+        acc(3.14159, weight = w);
+
+        std::cout << "  mean(acc)       = " << mean(acc) << std::endl;
+    }
+
+    // Weighted calculation with an external weight accumulator
+    {
+        // stats that depend on the weight are made external
+        accumulator_set<double, stats<tag::mean>, external<double> > acc;
+
+        // Here's an external weight accumulator
+        accumulator_set<void, stats<tag::sum_of_weights>, double> weight_acc;
+
+        weight_acc(weight = w); acc(0., weight = w);
+        weight_acc(weight = w); acc(1., weight = w);
+        weight_acc(weight = w); acc(-1., weight = w);
+        weight_acc(weight = w); acc(3.14159, weight = w);
+
+        std::cout << "  mean(acc)       = " << mean(acc, weights = weight_acc) << std::endl;
+    }
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// main
+int main()
+{
+    std::cout << "Example 1:\n";
+    example1();
+
+    std::cout << "\nExample 2:\n";
+    example2();
+
+    std::cout << "\nExample 3:\n";
+    example3();
+
+    return 0;
+}

Added: trunk/libs/accumulators/index.html
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/index.html	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,15 @@
+<html>
+<head>
+<meta http-equiv="refresh" content="0; URL=../../doc/html/accumulators.html">
+</head>
+<body>
+Automatic redirection failed, please go to
+../../doc/html/accumulators.html
+<p>Copyright&nbsp;Eric Niebler 2006</p>
+<p>Distributed under the Boost Software License, Version 1.0. (See accompanying file
+LICENSE_1_0.txt or copy at
+www.boost.org/LICENSE_1_0.txt).
+</p>
+</body>
+</html>
+

Added: trunk/libs/accumulators/test/Jamfile.v2
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/Jamfile.v2	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,73 @@
+# (C) Copyright 2005: Eric Niebler
+# Distributed under the Boost Software License, Version 1.0.
+# (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+# bring in rules for testing
+import testing ;
+import feature ;
+
+feature.feature iterator_debugging
+  : on off
+  : composite propagated optional
+  ;
+
+feature.compose <iterator_debugging>off
+  : <define>_HAS_ITERATOR_DEBUGGING=0
+  ;
+
+project
+    : requirements
+      <library>/boost/test//boost_unit_test_framework
+      <link>static
+      <include>../../..
+      <toolset>msvc-8.0:<define>_SCL_SECURE_NO_DEPRECATE
+      # MSVC-8's iterator debugging causes some tests to run forever.
+      <toolset>msvc-8.0:<iterator_debugging>off
+    ;
+
+test-suite "accumulators"
+    : [ run count.cpp ]
+      [ run covariance.cpp ]
+      [ run droppable.cpp ]
+      [ run error_of.cpp ]
+      [ run extended_p_square.cpp ]
+      [ run extended_p_square_quantile.cpp ]
+      [ run external_accumulator.cpp ]
+      [ run external_weights.cpp ]
+      [ run kurtosis.cpp ]
+      [ run max.cpp ]
+      [ run mean.cpp ]
+      [ run median.cpp ]
+      [ run min.cpp ]
+      [ run moment.cpp ]
+      [ run pot_quantile.cpp ]
+      [ run p_square_cumulative_distribution.cpp ]
+      [ run p_square_quantile.cpp ]
+      [ run reference.cpp ]
+      [ run skewness.cpp ]
+      [ run sum.cpp ]
+      [ run tail.cpp ]
+      [ run tail_mean.cpp ]
+      [ run tail_quantile.cpp ]
+      [ run tail_variate_means.cpp ]
+      [ run valarray.cpp ]
+      [ run variance.cpp ]
+      [ run vector.cpp ]
+      [ run weighted_covariance.cpp ]
+      [ run weighted_extended_p_square.cpp ]
+      [ run weighted_kurtosis.cpp ]
+      [ run weighted_mean.cpp ]
+      [ run weighted_median.cpp ]
+      [ run weighted_moment.cpp ]
+      [ run weighted_p_square_cum_dist.cpp ]
+      [ run weighted_p_square_quantile.cpp ]
+      [ run weighted_skewness.cpp ]
+      [ run weighted_sum.cpp ]
+      [ run weighted_variance.cpp ]
+
+      [ run weighted_pot_quantile.cpp ]
+      [ run weighted_tail_mean.cpp ]
+      [ run weighted_tail_quantile.cpp ]
+      [ run weighted_tail_variate_means.cpp ]
+
+    ;

Added: trunk/libs/accumulators/test/count.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/count.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,48 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/count.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    accumulator_set<int, stats<tag::count> > acc;
+
+    acc(1);
+    BOOST_CHECK_EQUAL(1u, count(acc));
+
+    acc(1);
+    BOOST_CHECK_EQUAL(2u, count(acc));
+
+    acc(1);
+    BOOST_CHECK_EQUAL(3u, count(acc));
+
+    acc(1);
+    BOOST_CHECK_EQUAL(4u, count(acc));
+
+    acc(1);
+    BOOST_CHECK_EQUAL(5u, count(acc));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("count test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/covariance.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/covariance.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,101 @@
+//  (C) Copyright 2005 Daniel Egloff, Eric Niebler
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_NUMERIC_FUNCTIONAL_STD_VECTOR_SUPPORT
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/variates/covariate.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/covariance.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    std::vector<double> dummy;
+    dummy.push_back(0);
+    dummy.push_back(0);
+    
+    accumulator_set<double, stats<tag::covariance<double, tag::covariate1> > > acc;
+    accumulator_set<std::vector<double>, stats<tag::covariance<double, tag::covariate1> > > acc2(sample = dummy);
+    accumulator_set<double, stats<tag::covariance<std::vector<double>, tag::covariate1> > > acc3(covariate1 = dummy);
+    accumulator_set<std::vector<double>, stats<tag::covariance<std::vector<double>, tag::covariate1> > > acc4(sample = dummy, covariate1 = dummy);
+    
+    std::vector<double> a;
+    a.push_back(1.);
+    a.push_back(2.);
+    std::vector<double> b;
+    b.push_back(3.);
+    b.push_back(4.);
+    std::vector<double> c;
+    c.push_back(2.);
+    c.push_back(5.);
+    std::vector<double> d;
+    d.push_back(4.);
+    d.push_back(2.);
+    
+    // double - double
+    {
+        acc(1., covariate1 = 2.);
+        acc(1., covariate1 = 4.);
+        acc(2., covariate1 = 3.);
+        acc(6., covariate1 = 1.);
+    }
+    
+    // vector - double
+    {
+        acc2(a, covariate1 = 1.);
+        acc2(b, covariate1 = 1.);
+        acc2(c, covariate1 = 2.);
+        acc2(d, covariate1 = 6.);
+    }
+    
+    // double - vector
+    {
+        acc3(1., covariate1 = a);
+        acc3(1., covariate1 = b);
+        acc3(2., covariate1 = c);
+        acc3(6., covariate1 = d);
+    }
+    
+    // vector - vector
+    {
+        acc4(a, covariate1 = b);
+        acc4(b, covariate1 = c);
+        acc4(a, covariate1 = c);
+        acc4(d, covariate1 = b);
+    }
+    
+    double epsilon = 1e-6;
+    
+    BOOST_CHECK_CLOSE((covariance(acc)), -1.75, epsilon);
+    BOOST_CHECK_CLOSE((covariance(acc2))[0], 1.75, epsilon);
+    BOOST_CHECK_CLOSE((covariance(acc2))[1], -1.125, epsilon);
+    BOOST_CHECK_CLOSE((covariance(acc3))[0], 1.75, epsilon);
+    BOOST_CHECK_CLOSE((covariance(acc3))[1], -1.125, epsilon);
+    BOOST_CHECK_CLOSE((covariance(acc4))(0,0), 0.125, epsilon);
+    BOOST_CHECK_CLOSE((covariance(acc4))(0,1), -0.25, epsilon);
+    BOOST_CHECK_CLOSE((covariance(acc4))(1,0), -0.125, epsilon);
+    BOOST_CHECK_CLOSE((covariance(acc4))(1,1), 0.25, epsilon);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("covariance test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/droppable.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/droppable.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,142 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/mean.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+template<typename T>
+void assert_is_double(T const &)
+{
+    BOOST_MPL_ASSERT((is_same<T, double>));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    accumulator_set<int, stats<droppable<tag::mean> > > acc, test_acc(sample = 0);
+
+    acc(1);
+    BOOST_CHECK_CLOSE(1., mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+
+    acc(0);
+    BOOST_CHECK_CLOSE(0.5, mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+
+    acc.drop<tag::mean>();
+
+    acc(2);
+    BOOST_CHECK_CLOSE(0.5, mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+
+    assert_is_double(mean(acc));
+
+
+    accumulator_set<int, stats<droppable<tag::mean(immediate)> > > acc2, test_acc2(sample = 0);
+
+    acc2(1);
+    BOOST_CHECK_CLOSE(1., mean(acc2), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc2));
+
+    acc2(0);
+    BOOST_CHECK_CLOSE(0.5, mean(acc2), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc2));
+
+    acc2.drop<tag::mean>();
+
+    acc2(2);
+    BOOST_CHECK_CLOSE(0.5, mean(acc2), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc2));
+
+    assert_is_double(mean(acc2));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat2
+//
+void test_stat2()
+{
+    accumulator_set<int, stats<droppable<tag::sum>, droppable<tag::mean> > > acc, test_acc(sample = 0);
+
+    acc(1);
+    BOOST_CHECK_CLOSE(1., mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+
+    acc(0);
+    BOOST_CHECK_CLOSE(0.5, mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+
+    acc.drop<tag::mean>();
+    acc.drop<tag::sum>();
+
+    acc(2);
+    BOOST_CHECK_CLOSE(0.5, mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+
+    assert_is_double(mean(acc));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat3
+//
+void test_stat3()
+{
+    accumulator_set<int, stats<droppable<tag::sum>, droppable<tag::count>, droppable<tag::mean> > > acc, test_acc(sample = 0);
+
+    acc(1);
+    BOOST_CHECK_CLOSE(1., mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+
+    acc(0);
+    BOOST_CHECK_CLOSE(0.5, mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+
+    acc.drop<tag::mean>();
+    acc.drop<tag::sum>();
+
+    acc(2);
+    BOOST_CHECK_CLOSE(1./3., mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(3u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+
+    acc.drop<tag::count>();
+    acc(3);
+    BOOST_CHECK_CLOSE(1./3., mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(3u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+
+    assert_is_double(mean(acc));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("droppable test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+    test->add(BOOST_TEST_CASE(&test_stat2));
+    test->add(BOOST_TEST_CASE(&test_stat3));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/error_of.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/error_of.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,57 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/with_error.hpp>
+#include <boost/accumulators/statistics/error_of_mean.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    accumulator_set<double, stats<tag::error_of<tag::mean(lazy)> > > acc;
+    acc(1.1);
+    acc(1.2);
+    acc(1.3);
+    BOOST_CHECK_CLOSE(0.057735, error_of<tag::mean(lazy)>(acc), 1e-4);
+
+    accumulator_set<double, stats<tag::error_of<tag::mean(immediate)> > > acc2;
+    acc2(1.1);
+    acc2(1.2);
+    acc2(1.3);
+    BOOST_CHECK_CLOSE(0.057735, error_of<tag::mean(immediate)>(acc2), 1e-4);
+
+    accumulator_set<double, stats<with_error<tag::mean(lazy)> > > acc3;
+    acc3(1.1);
+    acc3(1.2);
+    acc3(1.3);
+    BOOST_CHECK_CLOSE(0.057735, error_of<tag::mean(lazy)>(acc3), 1e-4);
+
+    accumulator_set<double, stats<with_error<tag::mean(immediate)> > > acc4;
+    acc4(1.1);
+    acc4(1.2);
+    acc4(1.3);
+    BOOST_CHECK_CLOSE(0.057735, error_of<tag::mean(immediate)>(acc4), 1e-4);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("mean test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/extended_p_square.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/extended_p_square.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,74 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for extended_p_square.hpp
+
+#include <iostream>
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/extended_p_square.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    typedef accumulator_set<double, stats<tag::extended_p_square> > accumulator_t;
+
+    // tolerance
+    double epsilon = 2;
+
+    // a random number generator
+    boost::lagged_fibonacci607 rng;
+
+    std::vector<double> probs;
+
+    probs.push_back(0.001);
+    probs.push_back(0.01 );
+    probs.push_back(0.1  );
+    probs.push_back(0.25 );
+    probs.push_back(0.5  );
+    probs.push_back(0.75 );
+    probs.push_back(0.9  );
+    probs.push_back(0.99 );
+    probs.push_back(0.999);
+
+    accumulator_t acc(extended_p_square_probabilities = probs);
+
+    for (int i=0; i<10000; ++i)
+        acc(rng());
+
+    BOOST_CHECK_CLOSE(extended_p_square(acc)[0], probs[0], 25);
+    BOOST_CHECK_CLOSE(extended_p_square(acc)[1], probs[1], 10);
+    BOOST_CHECK_CLOSE(extended_p_square(acc)[2], probs[2], 5);
+    
+    for (std::size_t i=3; i<probs.size(); ++i)
+    {
+        BOOST_CHECK_CLOSE(extended_p_square(acc)[i], probs[i], epsilon);
+    }
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("extended_p_square test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/extended_p_square_quantile.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/extended_p_square_quantile.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,102 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for extended_p_square_quantile.hpp
+
+#include <iostream>
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/extended_p_square_quantile.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    typedef accumulator_set<double, stats<tag::extended_p_square_quantile> > accumulator_t;
+    typedef accumulator_set<double, stats<tag::weighted_extended_p_square_quantile>, double > accumulator_t_weighted;
+    typedef accumulator_set<double, stats<tag::extended_p_square_quantile(quadratic)> > accumulator_t_quadratic;
+    typedef accumulator_set<double, stats<tag::weighted_extended_p_square_quantile(quadratic)>, double > accumulator_t_weighted_quadratic;
+
+    // tolerance
+    double epsilon = 1;
+
+    // a random number generator
+    boost::lagged_fibonacci607 rng;
+
+    std::vector<double> probs;
+
+    probs.push_back(0.990);
+    probs.push_back(0.991);
+    probs.push_back(0.992);
+    probs.push_back(0.993);
+    probs.push_back(0.994);
+    probs.push_back(0.995);
+    probs.push_back(0.996);
+    probs.push_back(0.997);
+    probs.push_back(0.998);
+    probs.push_back(0.999);
+
+    accumulator_t acc(extended_p_square_probabilities = probs);
+    accumulator_t_weighted acc_weighted(extended_p_square_probabilities = probs);
+    accumulator_t_quadratic acc2(extended_p_square_probabilities = probs);
+    accumulator_t_weighted_quadratic acc_weighted2(extended_p_square_probabilities = probs);
+    
+    for (int i=0; i<10000; ++i)
+    {
+        double sample = rng();
+        acc(sample);
+        acc2(sample);
+        acc_weighted(sample, weight = 1.);
+        acc_weighted2(sample, weight = 1.);
+    }
+    
+    for (std::size_t i = 0; i < probs.size() - 1; ++i)
+    {
+        BOOST_CHECK_CLOSE(
+            quantile(acc, quantile_probability = 0.99025 + i*0.001)
+          , 0.99025 + i*0.001
+          , epsilon
+        );
+        BOOST_CHECK_CLOSE(
+            quantile(acc2, quantile_probability = 0.99025 + i*0.001)
+          , 0.99025 + i*0.001
+          , epsilon
+        );
+        BOOST_CHECK_CLOSE(
+            quantile(acc_weighted, quantile_probability = 0.99025 + i*0.001)
+          , 0.99025 + i*0.001
+          , epsilon
+        );
+        BOOST_CHECK_CLOSE(
+            quantile(acc_weighted2, quantile_probability = 0.99025 + i*0.001)
+          , 0.99025 + i*0.001
+          , epsilon
+        );
+    }
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("extended_p_square_quantile test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/external_accumulator.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/external_accumulator.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,129 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/mean.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+namespace my
+{
+    BOOST_PARAMETER_KEYWORD(tag, sum_acc)
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    accumulator_set<int, stats<tag::mean, tag::external<tag::sum, my::tag::sum_acc> > > acc;
+    accumulator_set<int, stats<tag::sum> > sum_acc;
+
+    acc(1);
+    sum_acc(1);
+    BOOST_CHECK_CLOSE(1., mean(acc, my::sum_acc = sum_acc), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(sum_acc));
+
+    acc(0);
+    sum_acc(0);
+    BOOST_CHECK_CLOSE(0.5, mean(acc, my::sum_acc = sum_acc), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc, my::sum_acc = sum_acc));
+
+    acc(2);
+    sum_acc(2);
+    BOOST_CHECK_CLOSE(1., mean(acc, my::sum_acc = sum_acc), 1e-5);
+    BOOST_CHECK_EQUAL(3u, count(acc));
+    BOOST_CHECK_EQUAL(3, sum(acc, my::sum_acc = sum_acc));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_reference
+//
+void test_reference()
+{
+    typedef accumulator_set<int, stats<tag::sum> > sum_acc_type;
+    sum_acc_type sum_acc;
+    accumulator_set<
+        int
+      , stats<
+            tag::mean
+          , tag::external<tag::sum, my::tag::sum_acc>
+          , tag::reference<sum_acc_type, my::tag::sum_acc>
+        >
+    > acc(my::sum_acc = sum_acc);
+
+    acc(1);
+    sum_acc(1);
+    BOOST_CHECK_CLOSE(1., mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(sum_acc));
+
+    acc(0);
+    sum_acc(0);
+    BOOST_CHECK_CLOSE(0.5, mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+
+    acc(2);
+    sum_acc(2);
+    BOOST_CHECK_CLOSE(1., mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(3u, count(acc));
+    BOOST_CHECK_EQUAL(3, sum(acc));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_reference2
+//
+void test_reference2()
+{
+    typedef accumulator_set<int, stats<tag::sum> > sum_acc_type;
+    sum_acc_type sum_acc;
+    accumulator_set<
+        int
+      , stats<
+            tag::mean
+          , tag::external<tag::sum, my::tag::sum_acc, sum_acc_type>
+        >
+    > acc(my::sum_acc = sum_acc);
+
+    acc(1);
+    sum_acc(1);
+    BOOST_CHECK_CLOSE(1., mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(sum_acc));
+
+    acc(0);
+    sum_acc(0);
+    BOOST_CHECK_CLOSE(0.5, mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+
+    acc(2);
+    sum_acc(2);
+    BOOST_CHECK_CLOSE(1., mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(3u, count(acc));
+    BOOST_CHECK_EQUAL(3, sum(acc));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("external_accumulator test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+    test->add(BOOST_TEST_CASE(&test_reference));
+    test->add(BOOST_TEST_CASE(&test_reference2));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/external_weights.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/external_weights.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,54 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_mean.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    accumulator_set<int, stats<tag::weighted_mean>, external<int> > acc;
+    accumulator_set<void, stats<tag::sum_of_weights>, int> weight_acc;
+
+    acc(10, weight = 2);                        //  20
+    weight_acc(weight = 2);                     //
+    BOOST_CHECK_EQUAL(2, sum_of_weights(weight_acc));   //
+                                                //
+    acc(6, weight = 3);                         //  18
+    weight_acc(weight = 3);                     //
+    BOOST_CHECK_EQUAL(5, sum_of_weights(weight_acc));   //
+                                                //
+    acc(4, weight = 4);                         //  16
+    weight_acc(weight = 4);                     //
+    BOOST_CHECK_EQUAL(9, sum_of_weights(weight_acc));   //
+                                                //
+    acc(6, weight = 5);                         //+ 30
+    weight_acc(weight = 5);                     //
+    BOOST_CHECK_EQUAL(14, sum_of_weights(weight_acc));  //
+                                                //= 84  / 14 = 6
+
+    BOOST_CHECK_CLOSE(6., weighted_mean(acc, weights = weight_acc), 1e-5);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("external_weights test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/kurtosis.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/kurtosis.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,70 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for kurtosis.hpp
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/kurtosis.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // tolerance in %
+    // double epsilon = 1;
+    
+    accumulator_set<double, stats<tag::kurtosis > > acc1;
+    accumulator_set<int, stats<tag::kurtosis > > acc2;
+        
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(0,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+    
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        acc1(normal());
+    }
+    
+    // This check fails because epsilon is relative and not absolute
+    // BOOST_CHECK_CLOSE( kurtosis(acc1), 0., epsilon );          
+    
+    acc2(2);
+    acc2(7);
+    acc2(4);
+    acc2(9);
+    acc2(3);
+    
+    BOOST_CHECK_EQUAL( mean(acc2), 5 );
+    BOOST_CHECK_EQUAL( moment<2>(acc2), 159./5. );
+    BOOST_CHECK_EQUAL( moment<3>(acc2), 1171./5. );
+    BOOST_CHECK_EQUAL( moment<4>(acc2), 1863 );
+    BOOST_CHECK_CLOSE( kurtosis(acc2), -1.39965397924, 1e-6 );
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("kurtosis test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/max.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/max.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,42 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/max.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    accumulator_set<int, stats<tag::max> > acc;
+
+    acc(1);
+    BOOST_CHECK_EQUAL(1, (max)(acc));
+
+    acc(0);
+    BOOST_CHECK_EQUAL(1, (max)(acc));
+
+    acc(2);
+    BOOST_CHECK_EQUAL(2, (max)(acc));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("max test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/mean.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/mean.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,92 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_mean.hpp>
+#include <boost/accumulators/statistics/variates/covariate.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+template<typename T>
+void assert_is_double(T const &)
+{
+    BOOST_MPL_ASSERT((is_same<T, double>));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    accumulator_set<
+        int
+      , stats<
+            tag::mean
+          , tag::mean_of_variates<int, tag::covariate1>
+        >
+    > acc, test_acc(sample = 0);
+
+    acc(1, covariate1 = 3);
+    BOOST_CHECK_CLOSE(1., mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+    BOOST_CHECK_CLOSE(3., (mean_of_variates<int, tag::covariate1>(acc)), 1e-5);
+    
+    acc(0, covariate1 = 4);
+    BOOST_CHECK_CLOSE(0.5, mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc));
+    BOOST_CHECK_EQUAL(1, sum(acc));
+    BOOST_CHECK_CLOSE(3.5, (mean_of_variates<int, tag::covariate1>(acc)), 1e-5);
+
+    acc(2, covariate1 = 8);
+    BOOST_CHECK_CLOSE(1., mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(3u, count(acc));
+    BOOST_CHECK_EQUAL(3, sum(acc));
+    BOOST_CHECK_CLOSE(5., (mean_of_variates<int, tag::covariate1>(acc)), 1e-5);
+
+    assert_is_double(mean(acc));
+
+    accumulator_set<
+        int
+      , stats<
+            tag::mean(immediate)
+          , tag::mean_of_variates<int, tag::covariate1>(immediate)
+        >
+    > acc2, test_acc2(sample = 0);
+
+    acc2(1, covariate1 = 3);
+    BOOST_CHECK_CLOSE(1., mean(acc2), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc2));
+    BOOST_CHECK_CLOSE(3., (mean_of_variates<int, tag::covariate1>(acc2)), 1e-5);
+
+    acc2(0, covariate1 = 4);
+    BOOST_CHECK_CLOSE(0.5, mean(acc2), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc2));
+    BOOST_CHECK_CLOSE(3.5, (mean_of_variates<int, tag::covariate1>(acc2)), 1e-5);
+
+    acc2(2, covariate1 = 8);
+    BOOST_CHECK_CLOSE(1., mean(acc2), 1e-5);
+    BOOST_CHECK_EQUAL(3u, count(acc2));
+    BOOST_CHECK_CLOSE(5., (mean_of_variates<int, tag::covariate1>(acc2)), 1e-5);
+
+    assert_is_double(mean(acc2));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("mean test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/median.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/median.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,57 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/random.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/median.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // two random number generators
+    double mu = 1.;
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(mu,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+    
+    accumulator_set<double, stats<tag::median(with_p_square_quantile) > > acc;
+    accumulator_set<double, stats<tag::median(with_density) > > 
+        acc_dens( density_cache_size = 10000, density_num_bins = 1000 );
+    accumulator_set<double, stats<tag::median(with_p_square_cumulative_distribution) > > 
+        acc_cdist( p_square_cumulative_distribution_num_cells = 100 );
+        
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        double sample = normal();
+        acc(sample);
+        acc_dens(sample);
+        acc_cdist(sample);
+    }
+    
+    BOOST_CHECK_CLOSE(1., median(acc), 1.);
+    BOOST_CHECK_CLOSE(1., median(acc_dens), 1.);
+    BOOST_CHECK_CLOSE(1., median(acc_cdist), 3.);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("median test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/min.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/min.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,42 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/min.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    accumulator_set<int, stats<tag::min> > acc;
+
+    acc(1);
+    BOOST_CHECK_EQUAL(1, (min)(acc));
+
+    acc(0);
+    BOOST_CHECK_EQUAL(0, (min)(acc));
+
+    acc(2);
+    BOOST_CHECK_EQUAL(0, (min)(acc));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("min test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/moment.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/moment.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,52 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/moment.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    accumulator_set<int, stats<tag::moment<2> > > acc1;
+
+    acc1(2); //    4
+    acc1(4); //   16
+    acc1(5); // + 25
+             // = 45 / 3 = 15
+
+    BOOST_CHECK_CLOSE(15., moment<2>(acc1), 1e-5);
+
+    accumulator_set<int, stats<tag::moment<5> > > acc2;
+
+    acc2(2); //     32
+    acc2(3); //    243
+    acc2(4); //   1024
+    acc2(5); // + 3125
+             // = 4424 / 4 = 1106
+
+    BOOST_CHECK_CLOSE(1106., moment<5>(acc2), 1e-5);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("moment test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/p_square_cumulative_distribution.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/p_square_cumulative_distribution.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,81 @@
+//  (C) Copyright Eric Niebler, Olivier Gygi 2006.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for p_square_cumulative_distribution.hpp
+
+#include <cmath>
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/p_square_cumulative_distribution.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// erf() not known by VC++ compiler!
+// my_erf() computes error function by numerically integrating with trapezoidal rule
+//
+double my_erf(double const& x, int const& n = 1000)
+{
+    double sum = 0.;
+    double delta = x/n;
+    for (int i = 1; i < n; ++i)
+        sum += std::exp(-i*i*delta*delta) * delta;
+    sum += 0.5 * delta * (1. + std::exp(-x*x));
+    return sum * 2. / std::sqrt(3.141592653);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // tolerance in %
+    double epsilon = 3;
+
+    typedef accumulator_set<double, stats<tag::p_square_cumulative_distribution> > accumulator_t;
+        
+    accumulator_t acc(p_square_cumulative_distribution_num_cells = 100);
+    
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(0,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+    
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        acc(normal());
+    }
+    
+    typedef iterator_range<std::vector<std::pair<double, double> >::iterator > histogram_type;
+    histogram_type histogram = p_square_cumulative_distribution(acc);
+    
+    for (std::size_t i = 0; i < histogram.size(); ++i)
+    {   
+        // problem with small results: epsilon is relative (in percent), not absolute!
+        if ( histogram[i].second > 0.001 )    
+            BOOST_CHECK_CLOSE( 0.5 * (1.0 + my_erf( histogram[i].first / sqrt(2.0) )), histogram[i].second, epsilon );
+    }        
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("p_square_cumulative_distribution test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/p_square_quantile.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/p_square_quantile.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,81 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for p_square_quantile.hpp
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/p_square_quantile.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    typedef accumulator_set<double, stats<tag::p_square_quantile> > accumulator_t;
+
+    // tolerance in %
+    double epsilon = 1;
+    
+    // a random number generator
+    boost::lagged_fibonacci607 rng;
+  
+    accumulator_t acc0(quantile_probability = 0.001);
+    accumulator_t acc1(quantile_probability = 0.01 );
+    accumulator_t acc2(quantile_probability = 0.1  );
+    accumulator_t acc3(quantile_probability = 0.25 );
+    accumulator_t acc4(quantile_probability = 0.5  );
+    accumulator_t acc5(quantile_probability = 0.75 );
+    accumulator_t acc6(quantile_probability = 0.9  );
+    accumulator_t acc7(quantile_probability = 0.99 );
+    accumulator_t acc8(quantile_probability = 0.999);
+    
+    for (int i=0; i<100000; ++i)
+    {
+        double sample = rng();
+        acc0(sample);
+        acc1(sample);
+        acc2(sample);
+        acc3(sample);
+        acc4(sample);
+        acc5(sample);
+        acc6(sample);
+        acc7(sample);
+        acc8(sample);
+    }
+    
+    BOOST_CHECK_CLOSE( p_square_quantile(acc0), 0.001, 15*epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc1), 0.01 , 5*epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc2), 0.1  , epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc3), 0.25 , epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc4), 0.5  , epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc5), 0.75 , epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc6), 0.9  , epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc7), 0.99 , epsilon );
+    BOOST_CHECK_CLOSE( p_square_quantile(acc8), 0.999, epsilon );    
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("p_square_quantile test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/p_square_quantile_extended.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/p_square_quantile_extended.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,70 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for p_square_quantile_extended.hpp
+
+#include <iostream>
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/p_square_quantile_extended.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    typedef accumulator_set<double, stats<tag::p_square_quantile_extended> > accumulator_t;
+
+    // tolerance
+    double epsilon = 1e-6;
+
+    // a random number generator
+    boost::lagged_fibonacci607 rng;
+
+    std::vector<double> probs;
+
+    probs.push_back(0.001);
+    probs.push_back(0.01 );
+    probs.push_back(0.1  );
+    probs.push_back(0.25 );
+    probs.push_back(0.5  );
+    probs.push_back(0.75 );
+    probs.push_back(0.9  );
+    probs.push_back(0.99 );
+    probs.push_back(0.999);
+
+    accumulator_t acc(tag::p_square_quantile_extended::probabilities = probs);
+
+    for (int i=0; i<10000; ++i)
+        acc(rng());
+
+    for (std::size_t i=0; i<probs.size(); ++i)
+    {
+        BOOST_CHECK_CLOSE(p_square_quantile_extended(acc)[i], probs[i], epsilon);
+    }
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("p_square_quantile_extended test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/pot_quantile.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/pot_quantile.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,97 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for pot_quantile.hpp
+
+#define BOOST_NUMERIC_FUNCTIONAL_STD_COMPLEX_SUPPORT
+#define BOOST_NUMERIC_FUNCTIONAL_STD_VALARRAY_SUPPORT
+#define BOOST_NUMERIC_FUNCTIONAL_STD_VECTOR_SUPPORT
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics.hpp>
+#include <boost/accumulators/statistics/peaks_over_threshold.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // tolerance in %
+    double epsilon = 1.;
+
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(0,1);
+    boost::exponential_distribution<> lambda(1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::exponential_distribution<> > exponential(rng, lambda);
+    
+    accumulator_set<double, stats<tag::pot_quantile<right>(with_threshold_value)> > acc1(
+        pot_threshold_value = 3.
+    );
+    accumulator_set<double, stats<tag::pot_quantile<right>(with_threshold_probability)> > acc2(
+        right_tail_cache_size = 2000
+      , pot_threshold_probability = 0.99
+    );
+    accumulator_set<double, stats<tag::pot_quantile<left>(with_threshold_value)> > acc3(
+        pot_threshold_value = -3.
+    );
+    accumulator_set<double, stats<tag::pot_quantile<left>(with_threshold_probability)> > acc4(
+        left_tail_cache_size = 2000
+      , pot_threshold_probability = 0.01
+    );
+    
+    accumulator_set<double, stats<tag::pot_quantile<right>(with_threshold_value)> > acc5(
+        pot_threshold_value = 5.
+    );
+    accumulator_set<double, stats<tag::pot_quantile<right>(with_threshold_probability)> > acc6(
+        right_tail_cache_size = 2000
+      , pot_threshold_probability = 0.995
+    );
+    
+    for (std::size_t i = 0; i < 100000; ++i)
+    {
+        double sample = normal();
+        acc1(sample);
+        acc2(sample);
+        acc3(sample);
+        acc4(sample);
+    }
+    
+    for (std::size_t i = 0; i < 100000; ++i)
+    {
+        double sample = exponential();
+        acc5(sample);
+        acc6(sample);
+    }
+   
+    BOOST_CHECK_CLOSE( quantile(acc1, quantile_probability = 0.999), 3.090232, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability = 0.999), 3.090232, epsilon );  
+    BOOST_CHECK_CLOSE( quantile(acc3, quantile_probability = 0.001), -3.090232, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc4, quantile_probability = 0.001), -3.090232, epsilon );  
+    
+    BOOST_CHECK_CLOSE( quantile(acc5, quantile_probability = 0.999), 6.908, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc6, quantile_probability = 0.999), 6.908, epsilon );  
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("pot_quantile test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/reference.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/reference.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,95 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/mean.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+namespace my
+{
+    BOOST_PARAMETER_KEYWORD(tag, int_ref)
+    BOOST_PARAMETER_KEYWORD(tag, sum_acc)
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    int i = 0;
+    accumulator_set<double, stats<tag::reference<int, my::tag::int_ref> > > acc(
+        my::int_ref = i);
+
+    int &ref1 = reference<int, my::tag::int_ref>(acc);
+    int &ref2 = reference_tag<my::tag::int_ref>(acc);
+
+    BOOST_CHECK_EQUAL(&i, &ref1);
+    BOOST_CHECK_EQUAL(&i, &ref2);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_external
+//
+void test_external()
+{
+    typedef accumulator_set<int, stats<tag::sum> > sum_acc_type;
+    sum_acc_type sum_acc; // the sum accumulator
+    accumulator_set<
+        int
+      , stats<
+            tag::mean
+          , tag::external<tag::sum, my::tag::sum_acc>       // make sum external
+          , tag::reference<sum_acc_type, my::tag::sum_acc>  // and hold a reference to it
+        >
+    > acc_with_ref(my::sum_acc = sum_acc); // initialize the reference sum
+
+    sum_acc(1);
+    sum_acc(2); // sum is now 3 for both
+    
+    BOOST_CHECK_EQUAL(sum(acc_with_ref), sum(sum_acc));      
+    BOOST_CHECK_EQUAL(sum(acc_with_ref), 3);      
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_external2
+//
+void test_external2()
+{
+    typedef accumulator_set<int, stats<tag::sum> > sum_acc_type;
+    sum_acc_type sum_acc; // the sum accumulator
+    accumulator_set<
+        int
+      , stats<
+            tag::mean
+            // make sum external and hold a reference to it
+          , tag::external<tag::sum, my::tag::sum_acc, sum_acc_type> 
+        >
+    > acc_with_ref(my::sum_acc = sum_acc); // initialize the reference sum
+
+    sum_acc(1);
+    sum_acc(2); // sum is now 3 for both
+    
+    BOOST_CHECK_EQUAL(sum(acc_with_ref), sum(sum_acc));      
+    BOOST_CHECK_EQUAL(sum(acc_with_ref), 3);      
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("reference_accumulator test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+    test->add(BOOST_TEST_CASE(&test_external));
+    test->add(BOOST_TEST_CASE(&test_external2));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/skewness.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/skewness.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,69 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for skewness.hpp
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/skewness.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // tolerance in %
+    // double epsilon = 1;
+    
+    accumulator_set<double, stats<tag::skewness > > acc1;
+    accumulator_set<int, stats<tag::skewness > > acc2;
+        
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(0,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+    
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        acc1(normal());
+    }
+    
+    // This check fails because epsilon is relative and not absolute
+    // BOOST_CHECK_CLOSE( skewness(acc1), 0., epsilon );          
+    
+    acc2(2);
+    acc2(7);
+    acc2(4);
+    acc2(9);
+    acc2(3);
+    
+    BOOST_CHECK_EQUAL( mean(acc2), 5 );
+    BOOST_CHECK_EQUAL( moment<2>(acc2), 159./5. );
+    BOOST_CHECK_EQUAL( moment<3>(acc2), 1171./5. );
+    BOOST_CHECK_CLOSE( skewness(acc2), 0.406040288214, 1e-6 );
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("skewness test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/sum.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/sum.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,50 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/sum.hpp>
+#include <boost/accumulators/statistics/weighted_sum.hpp>
+#include <boost/accumulators/statistics/variates/covariate.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    accumulator_set<int, stats<tag::sum, tag::sum_of_weights, tag::sum_of_variates<int, tag::covariate1> >, int> acc;
+
+    acc(1, weight = 2, covariate1 = 3);
+    BOOST_CHECK_EQUAL(2, sum(acc));
+    BOOST_CHECK_EQUAL(2, sum_of_weights(acc));
+    BOOST_CHECK_EQUAL(3, sum_of_variates(acc));
+
+    acc(2, weight = 4, covariate1 = 6);
+    BOOST_CHECK_EQUAL(10, sum(acc));
+    BOOST_CHECK_EQUAL(6, sum_of_weights(acc));
+    BOOST_CHECK_EQUAL(9, sum_of_variates(acc));
+
+    acc(3, weight = 6, covariate1 = 9);
+    BOOST_CHECK_EQUAL(28, sum(acc));
+    BOOST_CHECK_EQUAL(12, sum_of_weights(acc));
+    BOOST_CHECK_EQUAL(18, sum_of_variates(acc));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("sum test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/tail.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/tail.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,126 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/foreach.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/tail.hpp>
+#include <boost/accumulators/statistics/tail_variate.hpp>
+#include <boost/accumulators/statistics/variates/covariate.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+template<typename Range>
+void check_tail(Range const &rng, char const *expected)
+{
+    BOOST_FOREACH(int i, rng)
+    {
+        if(!*expected)
+        {
+            BOOST_CHECK(false);
+            return;
+        }
+        BOOST_CHECK_EQUAL(i, *expected++);
+    }
+    BOOST_CHECK(!*expected);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_right_tail
+//
+void test_right_tail()
+{
+    accumulator_set<int, stats<tag::tail_weights<right>, tag::tail_variate<int, tag::covariate1, right> >, int > acc(
+        right_tail_cache_size = 4
+    );
+
+    acc(010, weight = 2, covariate1 = 3);
+    check_tail(tail(acc), "\10");
+    check_tail(tail_variate(acc), "\3");
+    check_tail(tail_weights(acc), "\2");
+
+    acc(020, weight = 7, covariate1 = 1);
+    check_tail(tail(acc), "\20\10");
+    check_tail(tail_variate(acc), "\1\3");
+    check_tail(tail_weights(acc), "\7\2");
+
+    acc(014, weight = 6, covariate1 = 4);
+    check_tail(tail(acc), "\20\14\10");
+    check_tail(tail_variate(acc), "\1\4\3");
+    check_tail(tail_weights(acc), "\7\6\2");
+
+    acc(030, weight = 4, covariate1 = 5);
+    check_tail(tail(acc), "\30\20\14\10");
+    check_tail(tail_variate(acc), "\5\1\4\3");
+    check_tail(tail_weights(acc), "\4\7\6\2");
+
+    acc(001, weight = 1, covariate1 = 9);
+    check_tail(tail(acc), "\30\20\14\10");
+    check_tail(tail_variate(acc), "\5\1\4\3");
+    check_tail(tail_weights(acc), "\4\7\6\2");
+
+    acc(011, weight = 3, covariate1 = 7);
+    check_tail(tail(acc), "\30\20\14\11");
+    check_tail(tail_variate(acc), "\5\1\4\7");
+    check_tail(tail_weights(acc), "\4\7\6\3");
+
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_left_tail
+//
+void test_left_tail()
+{
+    accumulator_set<int, stats<tag::tail_weights<left>, tag::tail_variate<int, tag::covariate1, left> >, int > acc(
+        left_tail_cache_size = 4
+    );
+
+    acc(010, weight = 2, covariate1 = 3);
+    check_tail(tail(acc), "\10");
+    check_tail(tail_variate(acc), "\3");
+    check_tail(tail_weights(acc), "\2");
+
+    acc(020, weight = 7, covariate1 = 1);
+    check_tail(tail(acc), "\10\20");
+    check_tail(tail_variate(acc), "\3\1");
+    check_tail(tail_weights(acc), "\2\7");
+
+    acc(014, weight = 6, covariate1 = 4);
+    check_tail(tail(acc), "\10\14\20");
+    check_tail(tail_variate(acc), "\3\4\1");
+    check_tail(tail_weights(acc), "\2\6\7");
+
+    acc(030, weight = 4, covariate1 = 5);
+    check_tail(tail(acc), "\10\14\20\30");
+    check_tail(tail_variate(acc), "\3\4\1\5");
+    check_tail(tail_weights(acc), "\2\6\7\4");
+
+    acc(001, weight = 1, covariate1 = 9);
+    check_tail(tail(acc), "\1\10\14\20");
+    check_tail(tail_variate(acc), "\x9\3\4\1");
+    check_tail(tail_weights(acc), "\1\2\6\7");
+
+    acc(011, weight = 3, covariate1 = 7);
+    check_tail(tail(acc), "\1\10\11\14");
+    check_tail(tail_variate(acc), "\x9\3\7\4");
+    check_tail(tail_weights(acc), "\1\2\3\6");
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("tail test");
+
+    test->add(BOOST_TEST_CASE(&test_right_tail));
+    test->add(BOOST_TEST_CASE(&test_left_tail));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/tail_mean.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/tail_mean.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,86 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for tail_mean.hpp
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/tail_mean.hpp>
+#include <boost/accumulators/statistics/tail_quantile.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // tolerance in %
+    double epsilon = 1;
+    
+    std::size_t n = 100000; // number of MC steps
+    std::size_t c =  10000; // cache size
+    
+    typedef accumulator_set<double, stats<tag::non_coherent_tail_mean<right>, tag::tail_quantile<right> > > accumulator_t_right1;
+    typedef accumulator_set<double, stats<tag::non_coherent_tail_mean<left>, tag::tail_quantile<left> > > accumulator_t_left1;
+    typedef accumulator_set<double, stats<tag::coherent_tail_mean<right>, tag::tail_quantile<right> > > accumulator_t_right2;
+    typedef accumulator_set<double, stats<tag::coherent_tail_mean<left>, tag::tail_quantile<left> > > accumulator_t_left2;
+
+    accumulator_t_right1 acc0( right_tail_cache_size = c );
+    accumulator_t_left1 acc1( left_tail_cache_size = c );
+    accumulator_t_right2 acc2( right_tail_cache_size = c );
+    accumulator_t_left2 acc3( left_tail_cache_size = c );
+    
+    // a random number generator
+    boost::lagged_fibonacci607 rng;
+                    
+    for (std::size_t i = 0; i < n; ++i)
+    {
+        double sample = rng();
+        acc0(sample);
+        acc1(sample);
+        acc2(sample);
+        acc3(sample);
+    }
+    
+    // check uniform distribution
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc0, quantile_probability = 0.95), 0.975, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc0, quantile_probability = 0.975), 0.9875, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc0, quantile_probability = 0.99), 0.995, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc0, quantile_probability = 0.999), 0.9995, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc1, quantile_probability = 0.05), 0.025, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc1, quantile_probability = 0.025), 0.0125, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc1, quantile_probability = 0.01), 0.005, 5 );
+    BOOST_CHECK_CLOSE( non_coherent_tail_mean(acc1, quantile_probability = 0.001), 0.0005, 10 );
+    BOOST_CHECK_CLOSE( tail_mean(acc2, quantile_probability = 0.95), 0.975, epsilon );
+    BOOST_CHECK_CLOSE( tail_mean(acc2, quantile_probability = 0.975), 0.9875, epsilon );
+    BOOST_CHECK_CLOSE( tail_mean(acc2, quantile_probability = 0.99), 0.995, epsilon );
+    BOOST_CHECK_CLOSE( tail_mean(acc2, quantile_probability = 0.999), 0.9995, epsilon );
+    BOOST_CHECK_CLOSE( tail_mean(acc3, quantile_probability = 0.05), 0.025, epsilon );
+    BOOST_CHECK_CLOSE( tail_mean(acc3, quantile_probability = 0.025), 0.0125, epsilon );
+    BOOST_CHECK_CLOSE( tail_mean(acc3, quantile_probability = 0.01), 0.005, 5 );
+    BOOST_CHECK_CLOSE( tail_mean(acc3, quantile_probability = 0.001), 0.0005, 10 );
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("tail_mean test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/tail_quantile.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/tail_quantile.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,85 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for tail_quantile.hpp
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/tail_quantile.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // tolerance in %
+    double epsilon = 1;
+    
+    std::size_t n = 100000; // number of MC steps
+    std::size_t c =  10000; // cache size
+        
+    typedef accumulator_set<double, stats<tag::tail_quantile<right> > > accumulator_t_right;
+    typedef accumulator_set<double, stats<tag::tail_quantile<left> > > accumulator_t_left;
+    
+    accumulator_t_right acc0( right_tail_cache_size = c );
+    accumulator_t_right acc1( right_tail_cache_size = c );
+    accumulator_t_left  acc2( left_tail_cache_size = c );
+    accumulator_t_left  acc3( left_tail_cache_size = c );
+                    
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(0,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+                    
+    for (std::size_t i = 0; i < n; ++i)
+    {
+        double sample1 = rng();
+        double sample2 = normal();
+        acc0(sample1);
+        acc1(sample2);
+        acc2(sample1);
+        acc3(sample2);
+    }
+    
+    // check uniform distribution
+    BOOST_CHECK_CLOSE( quantile(acc0, quantile_probability = 0.95 ), 0.95,  epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc0, quantile_probability = 0.975), 0.975, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc0, quantile_probability = 0.99 ), 0.99,  epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc0, quantile_probability = 0.999), 0.999, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability  = 0.05 ), 0.05,  2 );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability  = 0.025), 0.025, 2 );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability  = 0.01 ), 0.01,  3 );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability  = 0.001), 0.001, 20 );
+    
+    // check standard normal distribution
+    BOOST_CHECK_CLOSE( quantile(acc1, quantile_probability = 0.975),  1.959963, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc1, quantile_probability = 0.999),  3.090232, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc3, quantile_probability  = 0.025), -1.959963, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc3, quantile_probability  = 0.001), -3.090232, epsilon );
+    
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("tail_quantile test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/tail_variate_means.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/tail_variate_means.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,131 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for tail_variate_means.hpp
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/variates/covariate.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/tail_variate_means.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    std::size_t c = 5; // cache size
+    
+    typedef double variate_type;
+    typedef std::vector<variate_type> variate_set_type;
+    
+    typedef accumulator_set<double, stats<tag::tail_variate_means<right, variate_set_type, tag::covariate1>(relative)> > accumulator_t1;
+    typedef accumulator_set<double, stats<tag::tail_variate_means<right, variate_set_type, tag::covariate1>(absolute)> > accumulator_t2;
+    typedef accumulator_set<double, stats<tag::tail_variate_means<left, variate_set_type, tag::covariate1>(relative)> > accumulator_t3;
+    typedef accumulator_set<double, stats<tag::tail_variate_means<left, variate_set_type, tag::covariate1>(absolute)> > accumulator_t4;
+    
+    accumulator_t1 acc1( right_tail_cache_size = c );
+    accumulator_t2 acc2( right_tail_cache_size = c );
+    accumulator_t3 acc3( left_tail_cache_size = c );
+    accumulator_t4 acc4( left_tail_cache_size = c );
+    
+    variate_set_type cov1, cov2, cov3, cov4, cov5;
+    double c1[] = { 10., 20., 30., 40. }; // 100
+    double c2[] = { 26.,  4., 17.,  3. }; // 50
+    double c3[] = { 46., 64., 40., 50. }; // 200
+    double c4[] = {  1.,  3., 70.,  6. }; // 80
+    double c5[] = {  2.,  2.,  2., 14. }; // 20
+    cov1.assign(c1, c1 + sizeof(c1)/sizeof(variate_type));
+    cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type));
+    cov3.assign(c3, c3 + sizeof(c3)/sizeof(variate_type));
+    cov4.assign(c4, c4 + sizeof(c4)/sizeof(variate_type));
+    cov5.assign(c5, c5 + sizeof(c5)/sizeof(variate_type));            
+    
+    acc1(100., covariate1 = cov1);
+    acc1( 50., covariate1 = cov2);
+    acc1(200., covariate1 = cov3);
+    acc1( 80., covariate1 = cov4);
+    acc1( 20., covariate1 = cov5);
+    
+    acc2(100., covariate1 = cov1);
+    acc2( 50., covariate1 = cov2);
+    acc2(200., covariate1 = cov3);
+    acc2( 80., covariate1 = cov4);
+    acc2( 20., covariate1 = cov5);
+    
+    acc3(100., covariate1 = cov1);
+    acc3( 50., covariate1 = cov2);
+    acc3(200., covariate1 = cov3);
+    acc3( 80., covariate1 = cov4);
+    acc3( 20., covariate1 = cov5);
+    
+    acc4(100., covariate1 = cov1);
+    acc4( 50., covariate1 = cov2);
+    acc4(200., covariate1 = cov3);
+    acc4( 80., covariate1 = cov4);
+    acc4( 20., covariate1 = cov5);
+   
+    // check relative risk contributions
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.7).begin()     ), 14./75. ); // (10 + 46) / 300 = 14/75
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.7).begin() + 1),  7./25. ); // (20 + 64) / 300 =  7/25
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.7).begin() + 2),  7./30. ); // (30 + 40) / 300 =  7/30
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.7).begin() + 3),  3./10. ); // (40 + 50) / 300 =  3/10
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.3).begin()    ), 14./35. ); // (26 +  2) /  70 = 14/35
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.3).begin() + 1),  3./35. ); // ( 4 +  2) /  70 =  3/35
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.3).begin() + 2), 19./70. ); // (17 +  2) /  70 = 19/70
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.3).begin() + 3), 17./70. ); // ( 3 + 14) /  70 = 17/70
+    
+    // check absolute risk contributions
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.7).begin()    ), 28 ); // (10 + 46) / 2 = 28
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.7).begin() + 1), 42 ); // (20 + 64) / 2 = 42
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.7).begin() + 2), 35 ); // (30 + 40) / 2 = 35
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.7).begin() + 3), 45 ); // (40 + 50) / 2 = 45
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.3).begin()    ), 14 ); // (26 +  2) / 2 = 14
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.3).begin() + 1),  3 ); // ( 4 +  2) / 2 =  3
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.3).begin() + 2),9.5 ); // (17 +  2) / 2 =  9.5
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.3).begin() + 3),8.5 ); // ( 3 + 14) / 2 =  8.5
+    
+    // check relative risk contributions
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.9).begin()    ), 23./100. ); // 46/200 = 23/100
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.9).begin() + 1),  8./25.  ); // 64/200 =  8/25
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.9).begin() + 2),  1./5.   ); // 40/200 =  1/5
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc1, quantile_probability = 0.9).begin() + 3),  1./4.   ); // 50/200 =  1/4
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.1).begin()    ),  1./10.  ); //  2/ 20 =  1/10
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.1).begin() + 1),  1./10.  ); //  2/ 20 =  1/10
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.1).begin() + 2),  1./10.  ); //  2/ 20 =  1/10
+    BOOST_CHECK_EQUAL( *(relative_tail_variate_means(acc3, quantile_probability = 0.1).begin() + 3),  7./10.  ); // 14/ 20 =  7/10
+    
+    // check absolute risk contributions
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.9).begin()    ), 46 ); // 46
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.9).begin() + 1), 64 ); // 64
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.9).begin() + 2), 40 ); // 40
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc2, quantile_probability = 0.9).begin() + 3), 50 ); // 50
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.1).begin()    ),  2 ); //  2
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.1).begin() + 1),  2 ); //  2
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.1).begin() + 2),  2 ); //  2
+    BOOST_CHECK_EQUAL( *(tail_variate_means(acc4, quantile_probability = 0.1).begin() + 3), 14 ); // 14
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("tail_variate_means test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/valarray.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/valarray.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,180 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <valarray>
+#include <boost/utility/enable_if.hpp>
+#include <boost/type_traits/is_floating_point.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/min.hpp>
+#include <boost/accumulators/statistics/max.hpp>
+#include <boost/accumulators/statistics/mean.hpp>
+#include <boost/accumulators/statistics/weighted_mean.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+template<typename T>
+typename enable_if<is_floating_point<T> >::type is_equal_or_close(T const &left, T const &right)
+{
+    BOOST_CHECK_CLOSE(left, right, 1e-5);
+}
+
+template<typename T>
+typename disable_if<is_floating_point<T> >::type is_equal_or_close(T const &left, T const &right)
+{
+    BOOST_CHECK_EQUAL(left, right);
+}
+
+template<typename T>
+void is_equal(std::valarray<T> const &left, std::valarray<T> const &right)
+{
+    BOOST_CHECK_EQUAL(left.size(), right.size());
+    if(left.size() == right.size())
+    {
+        for(std::size_t i = 0; i < left.size(); ++i)
+        {
+            is_equal_or_close(left[i], right[i]);
+        }
+    }
+}
+
+namespace std
+{
+    template<typename T>
+    inline std::ostream &operator <<(std::ostream &sout, std::valarray<T> const &arr)
+    {
+        sout << '(';
+        for(std::size_t i = 0; i < arr.size(); ++i)
+        {
+            sout << arr[i] << ',';
+        }
+        sout << ')' << std::endl;
+        return sout;
+    }
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    typedef std::valarray<int> sample_t;
+
+    // test sum
+    {
+        accumulator_set<sample_t, stats<tag::sum> > acc(sample = sample_t(0,3));
+
+        acc(sample_t(1,3));
+        acc(sample_t(2,3));
+        acc(sample_t(3,3));
+
+        is_equal(sample_t(6,3), sum(acc));
+    }
+
+    // test min and max
+    {
+        int s1[] = {1,2,3}, s2[] = {0,3,4}, s3[] = {2,1,4}, min_res[] = {0,1,3}, max_res[] = {2,3,4};
+        accumulator_set<sample_t, stats<tag::min, tag::max> > acc(sample = sample_t(0,3));
+
+        acc(sample_t(s1,3));
+        acc(sample_t(s2,3));
+        acc(sample_t(s3,3));
+
+        is_equal(sample_t(min_res,3), (min)(acc));
+        is_equal(sample_t(max_res,3), (max)(acc));
+    }
+
+    // test mean(lazy) and mean(immediate)
+    {
+        accumulator_set<sample_t, stats<tag::mean> > acc(sample = sample_t(0,3));
+
+        acc(sample_t(1,3));
+        is_equal(std::valarray<double>(1., 3), mean(acc));
+        BOOST_CHECK_EQUAL(1u, count(acc));
+        is_equal(sample_t(1, 3), sum(acc));
+
+        acc(sample_t(0,3));
+        is_equal(std::valarray<double>(0.5, 3), mean(acc));
+        BOOST_CHECK_EQUAL(2u, count(acc));
+        is_equal(sample_t(1, 3), sum(acc));
+
+        acc(sample_t(2,3));
+        is_equal(std::valarray<double>(1., 3), mean(acc));
+        BOOST_CHECK_EQUAL(3u, count(acc));
+        is_equal(sample_t(3, 3), sum(acc));
+
+
+        accumulator_set<sample_t, stats<tag::mean(immediate)> > acc2(sample = sample_t(0,3));
+
+        acc2(sample_t(1,3));
+        is_equal(std::valarray<double>(1., 3), mean(acc2));
+        BOOST_CHECK_EQUAL(1u, count(acc2));
+
+        acc2(sample_t(0,3));
+        is_equal(std::valarray<double>(0.5, 3), mean(acc2));
+        BOOST_CHECK_EQUAL(2u, count(acc2));
+
+        acc2(sample_t(2,3));
+        is_equal(std::valarray<double>(1., 3), mean(acc2));
+        BOOST_CHECK_EQUAL(3u, count(acc2));
+    }
+
+    // test weighted_mean
+    {
+        accumulator_set<sample_t, stats<tag::weighted_mean>, int> acc(sample = sample_t(0,3));
+
+        acc(sample_t(10,3), weight = 2);            //  20
+        BOOST_CHECK_EQUAL(2, sum_of_weights(acc));  //
+                                                    //
+        acc(sample_t(6,3), weight = 3);             //  18
+        BOOST_CHECK_EQUAL(5, sum_of_weights(acc));  //
+                                                    //
+        acc(sample_t(4,3), weight = 4);             //  16
+        BOOST_CHECK_EQUAL(9, sum_of_weights(acc));  //
+                                                    //
+        acc(sample_t(6,3), weight = 5);             //+ 30
+        BOOST_CHECK_EQUAL(14, sum_of_weights(acc)); //
+                                                    //= 84  / 14 = 6
+
+        is_equal(std::valarray<double>(6.,3), weighted_mean(acc));
+
+
+        accumulator_set<sample_t, stats<tag::weighted_mean(immediate)>, int> acc2(sample = sample_t(0,3));
+
+        acc2(sample_t(10,3), weight = 2);           //  20
+        BOOST_CHECK_EQUAL(2, sum_of_weights(acc2)); //
+                                                    //
+        acc2(sample_t(6,3), weight = 3);            //  18
+        BOOST_CHECK_EQUAL(5, sum_of_weights(acc2)); //
+                                                    //
+        acc2(sample_t(4,3), weight = 4);            //  16
+        BOOST_CHECK_EQUAL(9, sum_of_weights(acc2)); //
+                                                    //
+        acc2(sample_t(6,3), weight = 5);            //+ 30
+        BOOST_CHECK_EQUAL(14, sum_of_weights(acc2));//
+                                                    //= 84  / 14 = 6
+
+        is_equal(std::valarray<double>(6.,3), weighted_mean(acc2));
+
+    }
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("valarray test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/value.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/value.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,45 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+namespace my
+{
+    BOOST_PARAMETER_KEYWORD(tag, int_val)
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    int i = 42;
+    accumulator_set<double, stats<tag::value<int, my::tag::int_val> > > acc2(
+        my::int_val = i);
+
+    int val1 = value<int, my::tag::int_val>(acc2);
+    int val2 = value_tag<my::tag::int_val>(acc2);
+
+    BOOST_CHECK_EQUAL(i, val1);
+    BOOST_CHECK_EQUAL(i, val2);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("value_accumulator test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/variance.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/variance.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,68 @@
+//  (C) Copyright 2005 Daniel Egloff, Eric Niebler
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/variance.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // matlab
+    // >> samples = [1:5];
+    // >> mean(samples)
+    // ans = 3
+    // >> sum(samples .* samples) / length(samples)
+    // ans = 11  
+    // >> sum(samples .* samples) / length(samples) - mean(samples)^2
+    // ans = 2
+
+    // basic lazy variance
+    accumulator_set<int, stats<tag::variance > > acc1;
+
+    acc1(1);
+    acc1(2);
+    acc1(3);
+    acc1(4);
+    acc1(5);
+
+    BOOST_CHECK_EQUAL(5u, count(acc1));
+    BOOST_CHECK_CLOSE(3., mean(acc1), 1e-5);
+    BOOST_CHECK_CLOSE(11., moment<2>(acc1), 1e-5);
+    BOOST_CHECK_CLOSE(2., variance(acc1), 1e-5);
+
+    // immediate variance, now immediate with syntactic sugar, thanks to Eric
+    accumulator_set<int, stats<tag::variance(immediate) > > acc2;
+
+    acc2(1);
+    acc2(2);
+    acc2(3);
+    acc2(4);
+    acc2(5);
+
+    BOOST_CHECK_EQUAL(5u, count(acc2));
+    BOOST_CHECK_CLOSE(3., mean(acc2), 1e-5);
+    BOOST_CHECK_CLOSE(2., variance(acc2), 1e-5);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("variance test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/vector.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/vector.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,180 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <vector>
+#include <boost/utility/enable_if.hpp>
+#include <boost/type_traits/is_floating_point.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/min.hpp>
+#include <boost/accumulators/statistics/max.hpp>
+#include <boost/accumulators/statistics/mean.hpp>
+#include <boost/accumulators/statistics/weighted_mean.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+template<typename T>
+typename enable_if<is_floating_point<T> >::type is_equal_or_close(T const &left, T const &right)
+{
+    BOOST_CHECK_CLOSE(left, right, 1e-5);
+}
+
+template<typename T>
+typename disable_if<is_floating_point<T> >::type is_equal_or_close(T const &left, T const &right)
+{
+    BOOST_CHECK_EQUAL(left, right);
+}
+
+template<typename T>
+void is_equal(std::vector<T> const &left, std::vector<T> const &right)
+{
+    BOOST_CHECK_EQUAL(left.size(), right.size());
+    if(left.size() == right.size())
+    {
+        for(std::size_t i = 0; i < left.size(); ++i)
+        {
+            is_equal_or_close(left[i], right[i]);
+        }
+    }
+}
+
+namespace std
+{
+    template<typename T>
+    inline std::ostream &operator <<(std::ostream &sout, std::vector<T> const &arr)
+    {
+        sout << '(';
+        for(std::size_t i = 0; i < arr.size(); ++i)
+        {
+            sout << arr[i] << ',';
+        }
+        sout << ')' << std::endl;
+        return sout;
+    }
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    typedef std::vector<int> sample_t;
+
+    // test sum
+    {
+        accumulator_set<sample_t, stats<tag::sum> > acc(sample = sample_t(3,0));
+
+        acc(sample_t(3,1));
+        acc(sample_t(3,2));
+        acc(sample_t(3,3));
+
+        is_equal(sample_t(3,6), sum(acc));
+    }
+
+    // test min and max
+    {
+        int s1[] = {1,2,3}, s2[] = {0,3,4}, s3[] = {2,1,4}, min_res[] = {0,1,3}, max_res[] = {2,3,4};
+        accumulator_set<sample_t, stats<tag::min, tag::max> > acc(sample = sample_t(3,0));
+
+        acc(sample_t(s1,s1+3));
+        acc(sample_t(s2,s2+3));
+        acc(sample_t(s3,s3+3));
+
+        is_equal(sample_t(min_res,min_res+3), (min)(acc));
+        is_equal(sample_t(max_res,max_res+3), (max)(acc));
+    }
+
+    // test mean(lazy) and mean(immediate)
+    {
+        accumulator_set<sample_t, stats<tag::mean> > acc(sample = sample_t(3,0));
+
+        acc(sample_t(3,1));
+        is_equal(std::vector<double>(3, 1.), mean(acc));
+        BOOST_CHECK_EQUAL(1u, count(acc));
+        is_equal(sample_t(3,1), sum(acc));
+
+        acc(sample_t(3,0));
+        is_equal(std::vector<double>(3, 0.5), mean(acc));
+        BOOST_CHECK_EQUAL(2u, count(acc));
+        is_equal(sample_t(3,1), sum(acc));
+
+        acc(sample_t(3,2));
+        is_equal(std::vector<double>(3, 1.), mean(acc));
+        BOOST_CHECK_EQUAL(3u, count(acc));
+        is_equal(sample_t(3,3), sum(acc));
+
+
+        accumulator_set<sample_t, stats<tag::mean(immediate)> > acc2(sample = sample_t(3,0));
+
+        acc2(sample_t(3,1));
+        is_equal(std::vector<double>(3,1.), mean(acc2));
+        BOOST_CHECK_EQUAL(1u, count(acc2));
+
+        acc2(sample_t(3,0));
+        is_equal(std::vector<double>(3,0.5), mean(acc2));
+        BOOST_CHECK_EQUAL(2u, count(acc2));
+
+        acc2(sample_t(3,2));
+        is_equal(std::vector<double>(3,1.), mean(acc2));
+        BOOST_CHECK_EQUAL(3u, count(acc2));
+    }
+
+    // test weighted_mean
+    {
+        accumulator_set<sample_t, stats<tag::weighted_mean>, int> acc(sample = sample_t(3,0));
+
+        acc(sample_t(3,10), weight = 2);            //  20
+        BOOST_CHECK_EQUAL(2, sum_of_weights(acc));  //
+                                                    //
+        acc(sample_t(3,6), weight = 3);             //  18
+        BOOST_CHECK_EQUAL(5, sum_of_weights(acc));  //
+                                                    //
+        acc(sample_t(3,4), weight = 4);             //  16
+        BOOST_CHECK_EQUAL(9, sum_of_weights(acc));  //
+                                                    //
+        acc(sample_t(3,6), weight = 5);             //+ 30
+        BOOST_CHECK_EQUAL(14, sum_of_weights(acc)); //
+                                                    //= 84  / 14 = 6
+
+        is_equal(std::vector<double>(3,6.), weighted_mean(acc));
+
+
+        accumulator_set<sample_t, stats<tag::weighted_mean(immediate)>, int> acc2(sample = sample_t(3,0));
+
+        acc2(sample_t(3,10), weight = 2);           //  20
+        BOOST_CHECK_EQUAL(2, sum_of_weights(acc2)); //
+                                                    //
+        acc2(sample_t(3,6), weight = 3);            //  18
+        BOOST_CHECK_EQUAL(5, sum_of_weights(acc2)); //
+                                                    //
+        acc2(sample_t(3,4), weight = 4);            //  16
+        BOOST_CHECK_EQUAL(9, sum_of_weights(acc2)); //
+                                                    //
+        acc2(sample_t(3,6), weight = 5);            //+ 30
+        BOOST_CHECK_EQUAL(14, sum_of_weights(acc2));//
+                                                    //= 84  / 14 = 6
+
+        is_equal(std::vector<double>(3,6.), weighted_mean(acc2));
+
+    }
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("vector test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/weighted_covariance.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_covariance.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,101 @@
+//  (C) Copyright 2005 Daniel Egloff, Eric Niebler
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_NUMERIC_FUNCTIONAL_STD_VECTOR_SUPPORT
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/variates/covariate.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_covariance.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    std::vector<double> dummy;
+    dummy.push_back(0);
+    dummy.push_back(0);
+    
+    accumulator_set<double, stats<tag::weighted_covariance<double, tag::covariate1> >, double > acc;
+    accumulator_set<std::vector<double>, stats<tag::weighted_covariance<double, tag::covariate1> >, double > acc2(sample = dummy);
+    accumulator_set<double, stats<tag::weighted_covariance<std::vector<double>, tag::covariate1> >, double > acc3(covariate1 = dummy);
+    accumulator_set<std::vector<double>, stats<tag::weighted_covariance<std::vector<double>, tag::covariate1> >, double > acc4(sample = dummy, covariate1 = dummy);
+    
+    std::vector<double> a;
+    a.push_back(1.);
+    a.push_back(2.);
+    std::vector<double> b;
+    b.push_back(3.);
+    b.push_back(4.);
+    std::vector<double> c;
+    c.push_back(2.);
+    c.push_back(5.);
+    std::vector<double> d;
+    d.push_back(4.);
+    d.push_back(2.);
+    
+    // double - double
+    {
+        acc(1., weight = 1.1, covariate1 = 2.);
+        acc(1., weight = 2.2, covariate1 = 4.);
+        acc(2., weight = 3.3, covariate1 = 3.);
+        acc(6., weight = 4.4, covariate1 = 1.);        
+    }
+    
+    // vector - double
+    {
+        acc2(a, weight = 1.1, covariate1 = 1.);
+        acc2(b, weight = 2.2, covariate1 = 1.);
+        acc2(c, weight = 3.3, covariate1 = 2.);
+        acc2(d, weight = 4.4, covariate1 = 6.);
+    }
+    
+    // double - vector
+    {
+        acc3(1., weight = 1.1, covariate1 = a);
+        acc3(1., weight = 2.2, covariate1 = b);
+        acc3(2., weight = 3.3, covariate1 = c);
+        acc3(6., weight = 4.4, covariate1 = d);
+    }
+    
+    // vector - vector
+    {
+        acc4(a, weight = 1.1, covariate1 = b);
+        acc4(b, weight = 2.2, covariate1 = c);
+        acc4(a, weight = 3.3, covariate1 = c);
+        acc4(d, weight = 4.4, covariate1 = b);
+    }
+    
+    double epsilon = 1e-6;
+    
+    BOOST_CHECK_CLOSE((weighted_covariance(acc)), -2.39, epsilon);
+    BOOST_CHECK_CLOSE((weighted_covariance(acc2))[0], 1.93, epsilon);
+    BOOST_CHECK_CLOSE((weighted_covariance(acc2))[1], -2.09, epsilon);
+    BOOST_CHECK_CLOSE((weighted_covariance(acc3))[0], 1.93, epsilon);
+    BOOST_CHECK_CLOSE((weighted_covariance(acc3))[1], -2.09, epsilon);
+    BOOST_CHECK_CLOSE((weighted_covariance(acc4))(0,0), 0.4, epsilon);
+    BOOST_CHECK_CLOSE((weighted_covariance(acc4))(0,1), -0.2, epsilon);
+    BOOST_CHECK_CLOSE((weighted_covariance(acc4))(1,0), -0.4, epsilon);
+    BOOST_CHECK_CLOSE((weighted_covariance(acc4))(1,1), 0.2, epsilon);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_covariance test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/weighted_extended_p_square.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_extended_p_square.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,98 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for weighted_extended_p_square.hpp
+
+#include <iostream>
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_extended_p_square.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    typedef accumulator_set<double, stats<tag::weighted_extended_p_square>, double> accumulator_t;
+
+    // problem with small results: epsilon is relative (in percent), not absolute
+    
+    // tolerance in %
+    double epsilon = 1;
+
+    // some random number generators
+    double mu1 = -1.0;
+    double mu2 =  1.0;
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma1(mu1, 1);
+    boost::normal_distribution<> mean_sigma2(mu2, 1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal1(rng, mean_sigma1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal2(rng, mean_sigma2);
+
+    std::vector<double> probs_uniform, probs_normal1, probs_normal2, probs_normal_exact1, probs_normal_exact2;
+
+    double p1[] = {/*0.001,*/ 0.01, 0.1, 0.5, 0.9, 0.99, 0.999};
+    probs_uniform.assign(p1, p1 + sizeof(p1) / sizeof(double));
+    
+    double p2[] = {0.001, 0.025};
+    double p3[] = {0.975, 0.999};
+    probs_normal1.assign(p2, p2 + sizeof(p2) / sizeof(double));
+    probs_normal2.assign(p3, p3 + sizeof(p3) / sizeof(double));
+    
+    double p4[] = {-3.090232, -1.959963};
+    double p5[] = {1.959963, 3.090232};
+    probs_normal_exact1.assign(p4, p4 + sizeof(p4) / sizeof(double));
+    probs_normal_exact2.assign(p5, p5 + sizeof(p5) / sizeof(double));
+        
+    accumulator_t acc_uniform(extended_p_square_probabilities = probs_uniform);
+    accumulator_t acc_normal1(extended_p_square_probabilities = probs_normal1);
+    accumulator_t acc_normal2(extended_p_square_probabilities = probs_normal2);
+
+    for (std::size_t i = 0; i < 100000; ++i)
+    {
+        acc_uniform(rng(), weight = 1.);
+        
+        double sample1 = normal1();
+        double sample2 = normal2();
+        acc_normal1(sample1, weight = std::exp(-mu1 * (sample1 - 0.5 * mu1)));
+        acc_normal2(sample2, weight = std::exp(-mu2 * (sample2 - 0.5 * mu2)));
+    }
+    
+    // check for uniform distribution    
+    for (std::size_t i = 0; i < probs_uniform.size(); ++i)
+    {
+        BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_uniform)[i], probs_uniform[i], epsilon);
+    }
+    
+    // check for standard normal distribution
+    for (std::size_t i = 0; i < probs_normal1.size(); ++i)
+    {
+        BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_normal1)[i], probs_normal_exact1[i], epsilon);
+        BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_normal2)[i], probs_normal_exact2[i], epsilon);
+    }
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_extended_p_square test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/weighted_kurtosis.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_kurtosis.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,70 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for weighted_kurtosis.hpp
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_kurtosis.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // tolerance in %
+    // double epsilon = 1;
+    
+    accumulator_set<double, stats<tag::weighted_kurtosis>, double > acc1;
+    accumulator_set<int, stats<tag::weighted_kurtosis>, int > acc2;
+        
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(0,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+    
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        acc1(normal(), weight = rng());
+    }
+    
+    // This check fails because epsilon is relative and not absolute
+    // BOOST_CHECK_CLOSE( weighted_kurtosis(acc1), 0., epsilon );          
+    
+    acc2(2, weight = 4);
+    acc2(7, weight = 1);
+    acc2(4, weight = 3);
+    acc2(9, weight = 1);
+    acc2(3, weight = 2);
+    
+    BOOST_CHECK_EQUAL( weighted_mean(acc2), 42./11. );
+    BOOST_CHECK_EQUAL( weighted_moment<2>(acc2), 212./11. );
+    BOOST_CHECK_EQUAL( weighted_moment<3>(acc2), 1350./11. );
+    BOOST_CHECK_EQUAL( weighted_moment<4>(acc2), 9956./11. );
+    BOOST_CHECK_CLOSE( weighted_kurtosis(acc2), 0.58137026432, 1e-6 );
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_kurtosis test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/weighted_mean.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_mean.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,102 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_mean.hpp>
+#include <boost/accumulators/statistics/variates/covariate.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+template<typename T>
+void assert_is_double(T const &)
+{
+    BOOST_MPL_ASSERT((is_same<T, double>));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+        accumulator_set<
+        int
+      , stats<
+            tag::weighted_mean
+          , tag::mean_of_weights
+          , tag::weighted_mean_of_variates<int, tag::covariate1>
+        >
+      , int 
+    > acc, test_acc(sample = 0);
+
+    acc(1, weight = 2, covariate1 = 3);
+    BOOST_CHECK_CLOSE(1., weighted_mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc));
+    BOOST_CHECK_EQUAL(2, sum(acc));
+    BOOST_CHECK_CLOSE(2., mean_of_weights(acc), 1e-5);
+    BOOST_CHECK_CLOSE(3., (weighted_mean_of_variates<int, tag::covariate1>(acc)), 1e-5);
+
+    acc(0, weight = 4, covariate1 = 4);
+    BOOST_CHECK_CLOSE(1./3., weighted_mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc));
+    BOOST_CHECK_EQUAL(2, sum(acc));
+    BOOST_CHECK_CLOSE(3., mean_of_weights(acc), 1e-5);
+    BOOST_CHECK_CLOSE(11./3., (weighted_mean_of_variates<int, tag::covariate1>(acc)), 1e-5);
+
+    acc(2, weight = 9, covariate1 = 8);
+    BOOST_CHECK_CLOSE(4./3., weighted_mean(acc), 1e-5);
+    BOOST_CHECK_EQUAL(3u, count(acc));
+    BOOST_CHECK_EQUAL(20, sum(acc));
+    BOOST_CHECK_CLOSE(5., mean_of_weights(acc), 1e-5);
+    BOOST_CHECK_CLOSE(94./15., (weighted_mean_of_variates<int, tag::covariate1>(acc)), 1e-5);
+
+    assert_is_double(mean(acc));
+
+    accumulator_set<
+        int
+      , stats<
+            tag::weighted_mean(immediate)
+          , tag::mean_of_weights(immediate)
+          , tag::weighted_mean_of_variates<int, tag::covariate1>(immediate)
+        >
+      , int
+    > acc2, test_acc2(sample = 0);
+
+    acc2(1, weight = 2, covariate1 = 3);
+    BOOST_CHECK_CLOSE(1., weighted_mean(acc2), 1e-5);
+    BOOST_CHECK_EQUAL(1u, count(acc2));
+    BOOST_CHECK_CLOSE(2., mean_of_weights(acc2), 1e-5);
+    BOOST_CHECK_CLOSE(3., (weighted_mean_of_variates<int, tag::covariate1>(acc2)), 1e-5);
+        
+    acc2(0, weight = 4, covariate1 = 4);
+    BOOST_CHECK_CLOSE(1./3., weighted_mean(acc2), 1e-5);
+    BOOST_CHECK_EQUAL(2u, count(acc2));
+    BOOST_CHECK_CLOSE(3., mean_of_weights(acc2), 1e-5);
+    BOOST_CHECK_CLOSE(11./3., (weighted_mean_of_variates<int, tag::covariate1>(acc2)), 1e-5);
+    
+    acc2(2, weight = 9, covariate1 = 8);
+    BOOST_CHECK_CLOSE(4./3., weighted_mean(acc2), 1e-5);
+    BOOST_CHECK_EQUAL(3u, count(acc2));
+    BOOST_CHECK_CLOSE(5., mean_of_weights(acc2), 1e-5);
+    BOOST_CHECK_CLOSE(94./15., (mean_of_variates<int, tag::covariate1>(acc2)), 1e-5);
+
+    assert_is_double(mean(acc2));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_mean test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/weighted_median.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_median.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,64 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/random.hpp>
+#include <boost/range/iterator_range.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_median.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // Median estimation of normal distribution N(1,1) using samples from a narrow normal distribution N(1,0.01)
+    // The weights equal to the likelihood ratio of the corresponding samples
+    
+    // two random number generators
+    double mu = 1.;
+    double sigma_narrow = 0.01;
+    double sigma = 1.;
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma_narrow(mu,sigma_narrow);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal_narrow(rng, mean_sigma_narrow);
+    
+    accumulator_set<double, stats<tag::weighted_median(with_p_square_quantile) >, double > acc;
+    accumulator_set<double, stats<tag::weighted_median(with_density) >, double > 
+        acc_dens( density_cache_size = 10000, density_num_bins = 1000 );
+    accumulator_set<double, stats<tag::weighted_median(with_p_square_cumulative_distribution) >, double > 
+        acc_cdist( p_square_cumulative_distribution_num_cells = 100 );
+        
+        
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        double sample = normal_narrow();
+        acc(sample, weight = std::exp(0.5 * (sample - mu) * (sample - mu) * ( 1./sigma_narrow/sigma_narrow - 1./sigma/sigma )));
+        acc_dens(sample, weight = std::exp(0.5 * (sample - mu) * (sample - mu) * ( 1./sigma_narrow/sigma_narrow - 1./sigma/sigma )));
+        acc_cdist(sample, weight = std::exp(0.5 * (sample - mu) * (sample - mu) * ( 1./sigma_narrow/sigma_narrow - 1./sigma/sigma )));
+    }
+    
+    BOOST_CHECK_CLOSE(1., weighted_median(acc), 1e-1);
+    BOOST_CHECK_CLOSE(1., weighted_median(acc_dens), 1e-1);
+    BOOST_CHECK_CLOSE(1., weighted_median(acc_cdist), 1e-1);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_median test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/weighted_moment.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_moment.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,47 @@
+//  (C) Copyright Eric Niebler, Olivier Gygi 2006.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_moment.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    accumulator_set<double, stats<tag::weighted_moment<2> >, double> acc2;
+    accumulator_set<double, stats<tag::weighted_moment<7> >, double> acc7;
+        
+    acc2(2.1, weight = 0.7);
+    acc2(2.7, weight = 1.4);
+    acc2(1.8, weight = 0.9);
+    
+    acc7(2.1, weight = 0.7);
+    acc7(2.7, weight = 1.4);
+    acc7(1.8, weight = 0.9);
+        
+    BOOST_CHECK_CLOSE(5.403, weighted_moment<2>(acc2), 1e-5);
+    BOOST_CHECK_CLOSE(548.54182, weighted_moment<7>(acc7), 1e-5);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_moment test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/weighted_p_square_cum_dist.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_p_square_cum_dist.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,103 @@
+//  (C) Copyright Eric Niebler, Olivier Gygi 2006.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for weighted_p_square_cumulative_distribution.hpp
+
+#include <cmath>
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_p_square_cumulative_distribution.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// erf() not known by VC++ compiler!
+// my_erf() computes error function by numerically integrating with trapezoidal rule
+//
+double my_erf(double const& x, int const& n = 1000)
+{
+    double sum = 0.;
+    double delta = x/n;
+    for (int i = 1; i < n; ++i)
+        sum += std::exp(-i*i*delta*delta) * delta;
+    sum += 0.5 * delta * (1. + std::exp(-x*x));
+    return sum * 2. / std::sqrt(3.141592653);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // tolerance in %
+    double epsilon = 4;
+
+    typedef accumulator_set<double, stats<tag::weighted_p_square_cumulative_distribution>, double > accumulator_t;
+        
+    accumulator_t acc_upper(p_square_cumulative_distribution_num_cells = 100);
+    accumulator_t acc_lower(p_square_cumulative_distribution_num_cells = 100);
+    
+    // two random number generators
+    double mu_upper = 1.0;
+    double mu_lower = -1.0;
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma_upper(mu_upper,1);
+    boost::normal_distribution<> mean_sigma_lower(mu_lower,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal_upper(rng, mean_sigma_upper);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal_lower(rng, mean_sigma_lower);
+    
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        double sample = normal_upper();
+        acc_upper(sample, weight = std::exp(-mu_upper * (sample - 0.5 * mu_upper)));
+    }
+    
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        double sample = normal_lower();
+        acc_lower(sample, weight = std::exp(-mu_lower * (sample - 0.5 * mu_lower)));
+    }
+    
+    typedef iterator_range<std::vector<std::pair<double, double> >::iterator > histogram_type;
+    histogram_type histogram_upper = weighted_p_square_cumulative_distribution(acc_upper);
+    histogram_type histogram_lower = weighted_p_square_cumulative_distribution(acc_lower);
+    
+    // Note that applaying importance sampling results in a region of the distribution 
+    // to be estimated more accurately and another region to be estimated less accurately
+    // than without importance sampling, i.e., with unweighted samples
+    
+    for (std::size_t i = 0; i < histogram_upper.size(); ++i)
+    {   
+        // problem with small results: epsilon is relative (in percent), not absolute!
+        
+        // check upper region of distribution
+        if ( histogram_upper[i].second > 0.1 )    
+            BOOST_CHECK_CLOSE( 0.5 * (1.0 + my_erf( histogram_upper[i].first / sqrt(2.0) )), histogram_upper[i].second, epsilon );
+        // check lower region of distribution
+        if ( histogram_lower[i].second < -0.1 )    
+            BOOST_CHECK_CLOSE( 0.5 * (1.0 + my_erf( histogram_lower[i].first / sqrt(2.0) )), histogram_lower[i].second, epsilon );
+    }        
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_p_square_cumulative_distribution test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/weighted_p_square_quantile.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_p_square_quantile.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,100 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for weighted_p_square_quantile.hpp
+
+#include <cmath> // for std::exp()
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_p_square_quantile.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    typedef accumulator_set<double, stats<tag::weighted_p_square_quantile>, double> accumulator_t;
+
+    // tolerance in %
+    double epsilon = 1;
+    
+    // some random number generators
+    double mu4 = -1.0;
+    double mu5 = -1.0;
+    double mu6 = 1.0;
+    double mu7 = 1.0;
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma4(mu4, 1);
+    boost::normal_distribution<> mean_sigma5(mu5, 1);
+    boost::normal_distribution<> mean_sigma6(mu6, 1);
+    boost::normal_distribution<> mean_sigma7(mu7, 1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal4(rng, mean_sigma4);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal5(rng, mean_sigma5);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal6(rng, mean_sigma6);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal7(rng, mean_sigma7);
+        
+    accumulator_t acc0(quantile_probability = 0.001);
+    accumulator_t acc1(quantile_probability = 0.025);
+    accumulator_t acc2(quantile_probability = 0.975);
+    accumulator_t acc3(quantile_probability = 0.999);
+
+    accumulator_t acc4(quantile_probability = 0.001);
+    accumulator_t acc5(quantile_probability = 0.025);
+    accumulator_t acc6(quantile_probability = 0.975);
+    accumulator_t acc7(quantile_probability = 0.999);
+
+        
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        double sample = rng();
+        acc0(sample, weight = 1.);
+        acc1(sample, weight = 1.);
+        acc2(sample, weight = 1.);
+        acc3(sample, weight = 1.);
+        
+        double sample4 = normal4();
+        double sample5 = normal5();
+        double sample6 = normal6();
+        double sample7 = normal7();
+        acc4(sample4, weight = std::exp(-mu4 * (sample4 - 0.5 * mu4)));
+        acc5(sample5, weight = std::exp(-mu5 * (sample5 - 0.5 * mu5)));
+        acc6(sample6, weight = std::exp(-mu6 * (sample6 - 0.5 * mu6)));
+        acc7(sample7, weight = std::exp(-mu7 * (sample7 - 0.5 * mu7)));
+    }
+    // check for uniform distribution with weight = 1
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc0), 0.001, 15 );
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc1), 0.025, 5 );
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc2), 0.975, epsilon );
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc3), 0.999, epsilon );
+    
+    // check for shifted standard normal distribution ("importance sampling")
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc4), -3.090232, epsilon );
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc5), -1.959963, epsilon );
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc6),  1.959963, epsilon );
+    BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc7),  3.090232, epsilon );
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_p_square_quantile test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/weighted_pot_quantile.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_pot_quantile.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,104 @@
+//  (C) Copyright Eric Niebler 2005.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for pot_quantile.hpp (weighted feature)
+
+#define BOOST_NUMERIC_FUNCTIONAL_STD_COMPLEX_SUPPORT
+#define BOOST_NUMERIC_FUNCTIONAL_STD_VALARRAY_SUPPORT
+#define BOOST_NUMERIC_FUNCTIONAL_STD_VECTOR_SUPPORT
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // tolerance in %
+    double epsilon = 1.;
+
+    double mu1, mu2, l;
+    
+    mu1 = 1.;
+    mu2 = -1.;
+    l = 0.5;
+    
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma1(mu1,1);
+    boost::normal_distribution<> mean_sigma2(mu2,1);
+    boost::exponential_distribution<> lambda(l);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal1(rng, mean_sigma1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal2(rng, mean_sigma2);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::exponential_distribution<> > exponential(rng, lambda);
+    
+    accumulator_set<double, stats<tag::weighted_pot_quantile<right>(with_threshold_value)>, double > acc1(
+        pot_threshold_value = 3.
+    );
+    accumulator_set<double, stats<tag::weighted_pot_quantile<right>(with_threshold_probability)>, double > acc2(
+        right_tail_cache_size = 10000
+      , pot_threshold_probability = 0.99
+    );
+    accumulator_set<double, stats<tag::weighted_pot_quantile<left>(with_threshold_value)>, double > acc3(
+        pot_threshold_value = -3.
+    );
+    accumulator_set<double, stats<tag::weighted_pot_quantile<left>(with_threshold_probability)>, double > acc4(
+        left_tail_cache_size = 10000
+      , pot_threshold_probability = 0.01
+    );
+    
+    accumulator_set<double, stats<tag::weighted_pot_quantile<right>(with_threshold_value)>, double > acc5(
+        pot_threshold_value = 5.
+    );
+    accumulator_set<double, stats<tag::weighted_pot_quantile<right>(with_threshold_probability)>, double > acc6(
+        right_tail_cache_size = 10000
+      , pot_threshold_probability = 0.995
+    );
+    
+    for (std::size_t i = 0; i < 100000; ++i)
+    {
+        double sample1 = normal1();
+        double sample2 = normal2();
+        acc1(sample1, weight = std::exp(-mu1 * (sample1 - 0.5 * mu1)));
+        acc2(sample1, weight = std::exp(-mu1 * (sample1 - 0.5 * mu1)));
+        acc3(sample2, weight = std::exp(-mu2 * (sample2 - 0.5 * mu2)));
+        acc4(sample2, weight = std::exp(-mu2 * (sample2 - 0.5 * mu2)));
+    }
+    
+    for (std::size_t i = 0; i < 100000; ++i)
+    {
+        double sample = exponential();
+        acc5(sample, weight = 1./l * std::exp(-sample * (1. - l)));
+        acc6(sample, weight = 1./l * std::exp(-sample * (1. - l)));
+    }
+   
+    BOOST_CHECK_CLOSE( quantile(acc1, quantile_probability = 0.999), 3.090232, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability = 0.999), 3.090232, epsilon );  
+    BOOST_CHECK_CLOSE( quantile(acc3, quantile_probability = 0.001), -3.090232, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc4, quantile_probability = 0.001), -3.090232, epsilon );  
+    
+    BOOST_CHECK_CLOSE( quantile(acc5, quantile_probability = 0.999), 6.908, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc6, quantile_probability = 0.999), 6.908, epsilon );  
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_pot_quantile test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/weighted_skewness.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_skewness.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,69 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for weighted_skewness.hpp
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/numeric/functional/vector.hpp>
+#include <boost/accumulators/numeric/functional/complex.hpp>
+#include <boost/accumulators/numeric/functional/valarray.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_skewness.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // tolerance in %
+    // double epsilon = 1;
+    
+    accumulator_set<double, stats<tag::weighted_skewness>, double > acc1;
+    accumulator_set<int, stats<tag::weighted_skewness>, int > acc2;
+        
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(0,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+    
+    for (std::size_t i=0; i<100000; ++i)
+    {
+        acc1(normal(), weight = rng());
+    }
+    
+    // This check fails because epsilon is relative and not absolute
+    // BOOST_CHECK_CLOSE( weighted_skewness(acc1), 0., epsilon );          
+    
+    acc2(2, weight = 4);
+    acc2(7, weight = 1);
+    acc2(4, weight = 3);
+    acc2(9, weight = 1);
+    acc2(3, weight = 2);
+    
+    BOOST_CHECK_EQUAL( weighted_mean(acc2), 42./11. );
+    BOOST_CHECK_EQUAL( weighted_moment<2>(acc2), 212./11. );
+    BOOST_CHECK_EQUAL( weighted_moment<3>(acc2), 1350./11. );
+    BOOST_CHECK_CLOSE( weighted_skewness(acc2), 1.30708406282, 1e-6 );
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_skewness test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/weighted_sum.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_sum.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,46 @@
+//  (C) Copyright Eric Niebler, Olivier Gygi 2006.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_sum.hpp>
+#include <boost/accumulators/statistics/variates/covariate.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    accumulator_set<int, stats<tag::weighted_sum, tag::weighted_sum_of_variates<int, tag::covariate1> >, int> acc;
+
+    acc(1, weight = 2, covariate1 = 3);
+    BOOST_CHECK_EQUAL(2, weighted_sum(acc));
+    BOOST_CHECK_EQUAL(6, weighted_sum_of_variates(acc));
+
+    acc(2, weight = 3, covariate1 = 6);
+    BOOST_CHECK_EQUAL(8, weighted_sum(acc));
+    BOOST_CHECK_EQUAL(24, weighted_sum_of_variates(acc));
+
+    acc(4, weight = 6, covariate1 = 9);
+    BOOST_CHECK_EQUAL(32, weighted_sum(acc));
+    BOOST_CHECK_EQUAL(78, weighted_sum_of_variates(acc));
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_sum test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Added: trunk/libs/accumulators/test/weighted_tail_mean.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_tail_mean.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,77 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for weighted_tail_mean.hpp
+
+#define BOOST_NUMERIC_FUNCTIONAL_STD_COMPLEX_SUPPORT
+#define BOOST_NUMERIC_FUNCTIONAL_STD_VALARRAY_SUPPORT
+#define BOOST_NUMERIC_FUNCTIONAL_STD_VECTOR_SUPPORT
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics.hpp>
+#include <boost/accumulators/statistics/weighted_tail_mean.hpp>
+#include <boost/accumulators/statistics/weighted_tail_quantile.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // tolerance in %
+    double epsilon = 1;
+    
+    std::size_t n = 100000; // number of MC steps
+    std::size_t c = 25000; // cache size
+    
+    accumulator_set<double, stats<tag::non_coherent_weighted_tail_mean<right> >, double >
+        acc0( right_tail_cache_size = c );
+    accumulator_set<double, stats<tag::non_coherent_weighted_tail_mean<left> >, double >
+        acc1( left_tail_cache_size = c );
+    
+    // random number generators
+    boost::lagged_fibonacci607 rng;
+    
+    for (std::size_t i = 0; i < n; ++i)
+    {
+        double smpl = std::sqrt(rng());
+        acc0(smpl, weight = 1./smpl);
+    }
+    
+    for (std::size_t i = 0; i < n; ++i)
+    {
+        double smpl = rng();
+        acc1(smpl*smpl, weight = smpl);
+    }
+    
+    // check uniform distribution
+    BOOST_CHECK_CLOSE( non_coherent_weighted_tail_mean(acc0, quantile_probability = 0.95), 0.975, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_weighted_tail_mean(acc0, quantile_probability = 0.975), 0.9875, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_weighted_tail_mean(acc0, quantile_probability = 0.99), 0.995, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_weighted_tail_mean(acc0, quantile_probability = 0.999), 0.9995, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_weighted_tail_mean(acc1, quantile_probability = 0.05), 0.025, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_weighted_tail_mean(acc1, quantile_probability = 0.025), 0.0125, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_weighted_tail_mean(acc1, quantile_probability = 0.01), 0.005, epsilon );
+    BOOST_CHECK_CLOSE( non_coherent_weighted_tail_mean(acc1, quantile_probability = 0.001), 0.0005, 5*epsilon );
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_tail_mean test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/weighted_tail_quantile.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_tail_quantile.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,75 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for weighted_tail_quantile.hpp
+
+#define BOOST_NUMERIC_FUNCTIONAL_STD_COMPLEX_SUPPORT
+#define BOOST_NUMERIC_FUNCTIONAL_STD_VALARRAY_SUPPORT
+#define BOOST_NUMERIC_FUNCTIONAL_STD_VECTOR_SUPPORT
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics.hpp>
+#include <boost/accumulators/statistics/weighted_tail_quantile.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // tolerance in %
+    double epsilon = 1;
+    
+    std::size_t n = 100000; // number of MC steps
+    std::size_t c =  20000; // cache size
+    
+    double mu1 = 1.0;
+    double mu2 = -1.0;
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma1(mu1,1);
+    boost::normal_distribution<> mean_sigma2(mu2,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal1(rng, mean_sigma1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal2(rng, mean_sigma2);
+    
+    accumulator_set<double, stats<tag::weighted_tail_quantile<right> >, double>
+        acc1(right_tail_cache_size = c);
+
+    accumulator_set<double, stats<tag::weighted_tail_quantile<left> >, double>
+        acc2(left_tail_cache_size = c);   
+    
+    for (std::size_t i = 0; i < n; ++i)
+    {
+        double sample1 = normal1();
+        double sample2 = normal2();
+        acc1(sample1, weight = std::exp(-mu1 * (sample1 - 0.5 * mu1)));
+        acc2(sample2, weight = std::exp(-mu2 * (sample2 - 0.5 * mu2)));
+    }
+    
+    // check standard normal distribution
+    BOOST_CHECK_CLOSE( quantile(acc1, quantile_probability = 0.975),  1.959963, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc1, quantile_probability = 0.999),  3.090232, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability  = 0.025), -1.959963, epsilon );
+    BOOST_CHECK_CLOSE( quantile(acc2, quantile_probability  = 0.001), -3.090232, epsilon );
+    
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_tail_quantile test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/weighted_tail_variate_means.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_tail_variate_means.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,131 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+// Test case for weighted_tail_variate_means.hpp
+
+#define BOOST_NUMERIC_FUNCTIONAL_STD_COMPLEX_SUPPORT
+#define BOOST_NUMERIC_FUNCTIONAL_STD_VALARRAY_SUPPORT
+#define BOOST_NUMERIC_FUNCTIONAL_STD_VECTOR_SUPPORT
+
+#include <boost/random.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/variates/covariate.hpp>
+#include <boost/accumulators/statistics.hpp>
+#include <boost/accumulators/statistics/weighted_tail_variate_means.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace boost::accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    std::size_t c = 5; // cache size
+    
+    typedef double variate_type;
+    typedef std::vector<variate_type> variate_set_type;
+    
+    accumulator_set<double, stats<tag::weighted_tail_variate_means<right, variate_set_type, tag::covariate1>(relative)>, double >
+        acc1( right_tail_cache_size = c );
+    accumulator_set<double, stats<tag::weighted_tail_variate_means<right, variate_set_type, tag::covariate1>(absolute)>, double >
+        acc2( right_tail_cache_size = c );
+    accumulator_set<double, stats<tag::weighted_tail_variate_means<left, variate_set_type, tag::covariate1>(relative)>, double >
+        acc3( left_tail_cache_size = c );
+    accumulator_set<double, stats<tag::weighted_tail_variate_means<left, variate_set_type, tag::covariate1>(absolute)>, double >
+        acc4( left_tail_cache_size = c );
+    
+    variate_set_type cov1, cov2, cov3, cov4, cov5;
+    double c1[] = { 10., 20., 30., 40. }; // 100
+    double c2[] = { 26.,  4., 17.,  3. }; // 50
+    double c3[] = { 46., 64., 40., 50. }; // 200
+    double c4[] = {  1.,  3., 70.,  6. }; // 80
+    double c5[] = {  2.,  2.,  2., 14. }; // 20
+    cov1.assign(c1, c1 + sizeof(c1)/sizeof(variate_type));
+    cov2.assign(c2, c2 + sizeof(c2)/sizeof(variate_type));
+    cov3.assign(c3, c3 + sizeof(c3)/sizeof(variate_type));
+    cov4.assign(c4, c4 + sizeof(c4)/sizeof(variate_type));
+    cov5.assign(c5, c5 + sizeof(c5)/sizeof(variate_type));            
+    
+    acc1(100., weight = 0.8, covariate1 = cov1);
+    acc1( 50., weight = 0.9, covariate1 = cov2);
+    acc1(200., weight = 1.0, covariate1 = cov3);
+    acc1( 80., weight = 1.1, covariate1 = cov4);
+    acc1( 20., weight = 1.2, covariate1 = cov5);
+    
+    acc2(100., weight = 0.8, covariate1 = cov1);
+    acc2( 50., weight = 0.9, covariate1 = cov2);
+    acc2(200., weight = 1.0, covariate1 = cov3);
+    acc2( 80., weight = 1.1, covariate1 = cov4);
+    acc2( 20., weight = 1.2, covariate1 = cov5);
+    
+    acc3(100., weight = 0.8, covariate1 = cov1);
+    acc3( 50., weight = 0.9, covariate1 = cov2);
+    acc3(200., weight = 1.0, covariate1 = cov3);
+    acc3( 80., weight = 1.1, covariate1 = cov4);
+    acc3( 20., weight = 1.2, covariate1 = cov5);
+    
+    acc4(100., weight = 0.8, covariate1 = cov1);
+    acc4( 50., weight = 0.9, covariate1 = cov2);
+    acc4(200., weight = 1.0, covariate1 = cov3);
+    acc4( 80., weight = 1.1, covariate1 = cov4);
+    acc4( 20., weight = 1.2, covariate1 = cov5);
+   
+    // check relative risk contributions
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc1, quantile_probability = 0.7).begin()    ), (0.8*10 + 1.0*46)/(0.8*100 + 1.0*200) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc1, quantile_probability = 0.7).begin() + 1), (0.8*20 + 1.0*64)/(0.8*100 + 1.0*200) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc1, quantile_probability = 0.7).begin() + 2), (0.8*30 + 1.0*40)/(0.8*100 + 1.0*200) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc1, quantile_probability = 0.7).begin() + 3), (0.8*40 + 1.0*50)/(0.8*100 + 1.0*200) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc3, quantile_probability = 0.3).begin()    ), (0.9*26 + 1.2*2)/(0.9*50 + 1.2*20) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc3, quantile_probability = 0.3).begin() + 1), (0.9*4 + 1.2*2)/(0.9*50 + 1.2*20) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc3, quantile_probability = 0.3).begin() + 2), (0.9*17 + 1.2*2)/(0.9*50 + 1.2*20) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc3, quantile_probability = 0.3).begin() + 3), (0.9*3 + 1.2*14)/(0.9*50 + 1.2*20) );
+    
+    // check absolute risk contributions
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc2, quantile_probability = 0.7).begin()    ), (0.8*10 + 1.0*46)/1.8 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc2, quantile_probability = 0.7).begin() + 1), (0.8*20 + 1.0*64)/1.8 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc2, quantile_probability = 0.7).begin() + 2), (0.8*30 + 1.0*40)/1.8 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc2, quantile_probability = 0.7).begin() + 3), (0.8*40 + 1.0*50)/1.8 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc4, quantile_probability = 0.3).begin()    ), (0.9*26 + 1.2*2)/2.1 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc4, quantile_probability = 0.3).begin() + 1), (0.9*4 + 1.2*2)/2.1 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc4, quantile_probability = 0.3).begin() + 2), (0.9*17 + 1.2*2)/2.1 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc4, quantile_probability = 0.3).begin() + 3), (0.9*3 + 1.2*14)/2.1 );
+    
+    // check relative risk contributions
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc1, quantile_probability = 0.9).begin()    ), 1.0*46/(1.0*200) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc1, quantile_probability = 0.9).begin() + 1), 1.0*64/(1.0*200) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc1, quantile_probability = 0.9).begin() + 2), 1.0*40/(1.0*200) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc1, quantile_probability = 0.9).begin() + 3), 1.0*50/(1.0*200) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc3, quantile_probability = 0.1).begin()    ), 1.2*2/(1.2*20) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc3, quantile_probability = 0.1).begin() + 1), 1.2*2/(1.2*20) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc3, quantile_probability = 0.1).begin() + 2), 1.2*2/(1.2*20) );
+    BOOST_CHECK_EQUAL( *(relative_weighted_tail_variate_means(acc3, quantile_probability = 0.1).begin() + 3), 1.2*14/(1.2*20) );
+    
+    // check absolute risk contributions
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc2, quantile_probability = 0.9).begin()    ), 1.0*46/1.0 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc2, quantile_probability = 0.9).begin() + 1), 1.0*64/1.0 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc2, quantile_probability = 0.9).begin() + 2), 1.0*40/1.0 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc2, quantile_probability = 0.9).begin() + 3), 1.0*50/1.0 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc4, quantile_probability = 0.1).begin()    ), 1.2*2/1.2 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc4, quantile_probability = 0.1).begin() + 1), 1.2*2/1.2 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc4, quantile_probability = 0.1).begin() + 2), 1.2*2/1.2 );
+    BOOST_CHECK_EQUAL( *(weighted_tail_variate_means(acc4, quantile_probability = 0.1).begin() + 3), 1.2*14/1.2 );
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_tail_variate_means test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}
+

Added: trunk/libs/accumulators/test/weighted_variance.cpp
==============================================================================
--- (empty file)
+++ trunk/libs/accumulators/test/weighted_variance.cpp	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -0,0 +1,81 @@
+//  (C) Copyright 2006 Eric Niebler, Olivier Gygi
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+#include <boost/random.hpp>
+#include <boost/accumulators/accumulators.hpp>
+#include <boost/accumulators/statistics/stats.hpp>
+#include <boost/accumulators/statistics/weighted_variance.hpp>
+
+using namespace boost;
+using namespace unit_test;
+using namespace accumulators;
+
+///////////////////////////////////////////////////////////////////////////////
+// test_stat
+//
+void test_stat()
+{
+    // basic lazy weighted_variance
+    accumulator_set<int, stats<tag::weighted_variance>, int> acc1;
+
+    acc1(1, weight = 2);    //  2
+    acc1(2, weight = 3);    //  6
+    acc1(3, weight = 1);    //  3
+    acc1(4, weight = 4);    // 16
+    acc1(5, weight = 1);    //  5
+
+    // weighted_mean = (2+6+3+16+5) / (2+3+1+4+1) = 32 / 11 = 2.9090909090909090909090909090909
+
+    BOOST_CHECK_EQUAL(5u, count(acc1));
+    BOOST_CHECK_CLOSE(2.9090909, weighted_mean(acc1), 1e-5);
+    BOOST_CHECK_CLOSE(10.1818182, weighted_moment<2>(acc1), 1e-5);
+    BOOST_CHECK_CLOSE(1.7190083, weighted_variance(acc1), 1e-5);
+
+    accumulator_set<int, stats<tag::weighted_variance(immediate)>, int> acc2;
+
+    acc2(1, weight = 2);
+    acc2(2, weight = 3);
+    acc2(3, weight = 1);
+    acc2(4, weight = 4);
+    acc2(5, weight = 1);
+
+    BOOST_CHECK_EQUAL(5u, count(acc2));
+    BOOST_CHECK_CLOSE(2.9090909, weighted_mean(acc2), 1e-5);
+    BOOST_CHECK_CLOSE(1.7190083, weighted_variance(acc2), 1e-5);
+    
+    // check lazy and immediate variance with random numbers
+    
+    // two random number generators
+    boost::lagged_fibonacci607 rng;
+    boost::normal_distribution<> mean_sigma(0,1);
+    boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal(rng, mean_sigma);
+    
+    accumulator_set<double, stats<tag::weighted_variance>, double > acc_lazy;    
+    accumulator_set<double, stats<tag::weighted_variance(immediate)>, double > acc_immediate;
+    
+    for (std::size_t i=0; i<10000; ++i)
+    {
+        double value = normal();
+        acc_lazy(value, weight = rng());
+        acc_immediate(value, weight = rng());
+    }
+    
+    BOOST_CHECK_CLOSE(1., weighted_variance(acc_lazy), 1.);
+    BOOST_CHECK_CLOSE(1., weighted_variance(acc_immediate), 1.);
+}
+
+///////////////////////////////////////////////////////////////////////////////
+// init_unit_test_suite
+//
+test_suite* init_unit_test_suite( int argc, char* argv[] )
+{
+    test_suite *test = BOOST_TEST_SUITE("weighted_variance test");
+
+    test->add(BOOST_TEST_CASE(&test_stat));
+
+    return test;
+}

Modified: trunk/status/Jamfile.v2
==============================================================================
--- trunk/status/Jamfile.v2	(original)
+++ trunk/status/Jamfile.v2	2008-01-02 15:55:20 EST (Wed, 02 Jan 2008)
@@ -24,6 +24,7 @@
 
 # Tests from Jamfiles in individual library test subdirectories
 # Please keep these in alphabetic order by test-suite name
+build-project ../libs/accumulators/test ;      # test-suite accumulators
 build-project ../libs/algorithm/minmax/test ;  # test-suite algorith/minmax
 build-project ../libs/algorithm/string/test ;  # test-suite algorithm/string
 build-project ../libs/asio/test ;              # test-suite asio