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From: Matthias Schabel (boost_at_[hidden])
Date: 2007-05-02 14:30:01

I'd like to congratulate John Maddock, Paul Bristow, and their
contributors on putting together an outstanding submission to Boost.
It is rare to have complete unanimity among votes, but in this case
there were no dissenters to accepting either the special functions or
the statistical distributions portions of the library, so I'm glad to
announce that it has been accepted for inclusion in Boost. Thanks to
the many participants in the review : Gottlob Frege, Guillaume
Melquiond, Johan Råde, Arnaldur Gylfason, John Phillips, Mark Van De
Vyver, Stephan Tolksdorf, Hubert Holin, Seweryn Habdank-Wojewodski,
Kevin Lynch, Leonaldo Peralta, Jeff Garland, and Stefan Seefeld
(apologies for anyone I might have missed in this list).

Here is a brief summary of the relatively few major issues that were
raised during the course of the review :

1) Error handling is an issue that arises because this library is at
the frontier between traditional numerical libraries and a
(hopefully) new breed of such libraries that utilize modern
programming techniques and facilities. Jeff Garland suggested that
the default behavior should be to throw an exception, with errno
being an option enabled by macro. It would also be nice to have more
granular control over which instances throw exceptions and which do
not (so, for example, a user could choose to ignore denormals). It
was also suggested that additional, more transparent exceptions be
provided for cases such as failure to converge rather than reusing

2) Jeff Garland also pointed out, rightly in my opinion, that
attempts to use statistical functions that do not exist for a
distribution should fail to compile rather than leading to a runtime
error (e.g. mean of a Cauchy distribution). A reasonable method of
implementing this should be devised or a strong argument for why it
is not feasible/desirable provided.

3) Arnaldur Gylfason did some nice accuracy and performance testing
vs. R. It was noted that the performance of quantile functions in
this library was significantly worse than R, unlike non-quantile
functions. He also pointed out that, for discrete distributions, the
current behavior of returning fractional results for quantiles may
not be the expected one. These issues should be addressed and

4) Hubert Holin suggested the possibility of use of a policy
parameter to choose between speed and accuracy. Another interesting
possibility would be to allow the user to specify the desired
precision either at compile or runtime.

5) It appears that this library will actually become two
"sublibraries" within the Boost.Math library. Currently all code
lives in the boost::math namespace; I would like to at least see a
discussion of the possibility of having
boost::math::special_functions, boost::math::statistics, and,
perhaps, boost::math::statistics::distributions namespaces - as more
functionality gets added to boost::math, collisions will become more
likely, so some thought given now to logical partitioning may save
pain later.

During the review a number of typos and minor issues of documentation
were raised, which the authors will need to address if they haven't
already. In particular, John Phillips noted that the rationale behind
using rational (vs. polynomial) approximations be clarified, the
derivation of coefficients be documented, and the list of special
functions in the documentation be expanded to encompass all functions
actually implemented in the library. Stephan Tolksdorf requested a
table listing standard statistical tests and the corresponding
library implementations and enumerated a number of other
documentation issues.

Overall, the library was very well received, and the authors are to
be commended on the tremendous amount of care and effort devoted to
its preparation.

Matthias Schabel
Review Manager

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