[Boost-commit] svn:boost r39032 - sandbox/math_toolkit/libs/math/example

From: pbristow_at_[hidden]
Date: 2007-08-28 09:22:00

Author: pbristow
Date: 2007-08-28 09:22:00 EDT (Tue, 28 Aug 2007)
New Revision: 39032
URL: http://svn.boost.org/trac/boost/changeset/39032

Log:
Removed file/folder
Removed:
   sandbox/math_toolkit/libs/math/example/binomial_example_NAG_C.cpp

Deleted: sandbox/math_toolkit/libs/math/example/binomial_example_NAG_C.cpp
==============================================================================
--- sandbox/math_toolkit/libs/math/example/binomial_example_NAG_C.cpp	2007-08-28 09:22:00 EDT (Tue, 28 Aug 2007)
+++ (empty file)
@@ -1,91 +0,0 @@
-// Copyright Paul A. 2007
-// Copyright John Maddock 2007
-// 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)
-
-// Simple example of computing probabilities for a binomial random variable.
-// Replication of source nag_binomial_dist (g01bjc).
-
-// Shows how to replace NAG C library calls by Boost Math Toolkit C++ calls.
-// Note that the default policy does not replicate the way that NAG
-// library calls handle 'bad' arguments, but you can define policies that do,
-// as well as other policies that may suit your application even better.
-// See the examples of changing default policies for details.
-
-#include <boost/math/distributions/binomial.hpp>
-
-#include <iostream>
-  using std::cout; using std::endl; using std::ios; using std::showpoint;
-#include <iomanip>
-  using std::fixed; using std::setw;
-
-int main()
-{
-  cout << "Using the binomial distribution to replicate a NAG library call." << endl;
-  using boost::math::binomial_distribution;
-
-  // This replicates the computation of the examples of using nag-binomial_dist
-  // using g01bjc in section g01 Somple Calculations on Statistical Data.
-  // http://www.nag.co.uk/numeric/cl/manual/pdf/G01/g01bjc.pdf
-  // Program results section 8.3 page 3.g01bjc.3
-    //8.2. Program Data
-    //g01bjc Example Program Data
-    //4 0.50 2 : n, p, k
-    //19 0.44 13
-    //100 0.75 67
-    //2000 0.33 700
-    //8.3. Program Results
-    //g01bjc Example Program Results
-    //n p k plek pgtk peqk
-    //4 0.500 2 0.68750 0.31250 0.37500
-    //19 0.440 13 0.99138 0.00862 0.01939
-    //100 0.750 67 0.04460 0.95540 0.01700
-    //2000 0.330 700 0.97251 0.02749 0.00312
-
-  cout.setf(ios::showpoint); // Trailing zeros to show significant decimal digits.
-  cout.precision(5); // Might calculate this from trials in distribution?
-  cout << fixed;
-  //  Binomial distribution.
-
-  // Note  that  cdf(dist, k) is equivalent to NAG library plek probability of <= k
-  // cdf(complement(dist, k)) is equivalent to NAG library pgtk probability of > k
-  //             pdf(dist, k) is equivalent to NAG library peqk probability of == k
-
-  cout << " n        p     k     plek     pgtk     peqk " << endl;
-  binomial_distribution<>my_dist(4, 0.5);
-  cout << setw(4) << (int)my_dist.trials() << "  " << my_dist.success_fraction()
-  << "   " << 2 << "  " << cdf(my_dist, 2) << "  "
-  << cdf(complement(my_dist, 2)) << "  " << pdf(my_dist, 2) << endl;
-
-  binomial_distribution<>two(19, 0.440);
-  cout << setw(4) << (int)two.trials() <<  "  "  << two.success_fraction()
-    << "  " << 13 << "  " << cdf(two, 13) << "  "
-    << cdf(complement(two, 13)) << "  " << pdf(two, 13) << endl;
-
-  binomial_distribution<>three(100, 0.750);
-  cout << setw(4) << (int)three.trials() << "  " << three.success_fraction()
-    << "  " << 67 << "  " << cdf(three, 67) << "  " << cdf(complement(three, 67))
-    << "  " << pdf(three, 67) << endl;
-  binomial_distribution<>four(2000, 0.330);
-  cout << setw(4) << (int)four.trials() <<  "  "  << four.success_fraction()
-  << " " << 700 << "  "
-    << cdf(four, 700) << "  " << cdf(complement(four, 700))
-    << "  " << pdf(four, 700) << endl;
-
-  return 0;
-} // int main()
-
-/*
-
-Example of using the binomial distribution to replicate a NAG library call.
- n        p     k     plek     pgtk     peqk
-   4  0.50000   2  0.68750  0.31250  0.37500
-  19  0.44000  13  0.99138  0.00862  0.01939
- 100  0.75000  67  0.04460  0.95540  0.01700
-2000  0.33000 700  0.97251  0.02749  0.00312
-
-
- */
-