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			94 lines
		
	
	
		
			3.8 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
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								[section:main_intro About the Math Toolkit]
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								This library is divided into three interconnected parts:
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								[h4 Statistical Distributions]
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								Provides a reasonably comprehensive set of
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								[link dist statistical distributions],
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								upon which higher level statistical tests can be built.
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								The initial focus is on the central
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								[@http://en.wikipedia.org/wiki/Univariate univariate ]
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								[@http://mathworld.wolfram.com/StatisticalDistribution.html distributions].
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								Both [@http://mathworld.wolfram.com/ContinuousDistribution.html continuous]
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								(like [link math_toolkit.dist_ref.dists.normal_dist normal]
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								& [link math_toolkit.dist_ref.dists.f_dist Fisher])
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								and [@http://mathworld.wolfram.com/DiscreteDistribution.html discrete]
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								(like [link math_toolkit.dist_ref.dists.binomial_dist binomial]
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								& [link math_toolkit.dist_ref.dists.poisson_dist Poisson])
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								distributions are provided.
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								A [link math_toolkit.stat_tut comprehensive tutorial is provided],
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								along with a series of
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								[link math_toolkit.stat_tut.weg worked examples] illustrating
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								how the library is used to conduct statistical tests.
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								[h4 Mathematical Special Functions]
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								Provides a small number of high quality
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								[link special special functions],
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								initially these were concentrated on functions used in statistical applications
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								along with those in the [tr1].
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								The function families currently implemented are the gamma, beta & erf functions
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								along with the incomplete gamma and beta functions (four variants
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								of each) and all the possible inverses of these, plus digamma,
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								various factorial functions,
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								Bessel functions, elliptic integrals, sinus cardinals (along with their
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								hyperbolic variants), inverse hyperbolic functions, Legrendre/Laguerre/Hermite
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								polynomials and various
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								special power and logarithmic functions.
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								All the implementations
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								are fully generic and support the use of arbitrary "real-number" types,
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								including __multiprecision,
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								although they are optimised for use with types with known-about
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								[@http://en.wikipedia.org/wiki/Significand significand (or mantissa)]
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								sizes: typically `float`, `double` or `long double`.
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								[h4 Implementation Toolkit]
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								The section [link math_toolkit.internals_overview Internal tools]
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								provides many of the tools required to implement
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								mathematical special functions: hopefully the presence of
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								these will encourage other authors to contribute more special
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								function implementations in the future.
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								Some tools are now considered well-tried and their signatures stable and unlikely to change.
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								There is a fairly comprehensive set of root finding both
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								__root_finding_without_derivatives
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								and __root_finding_with_derivatives with derivative support,
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								and function minimization using __brent_minima.
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								Other [link math_toolkit.internals_overview Internal tools]
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								are currently still considered experimental: they are "exposed implementation details"
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								whose interfaces and\/or implementations may change without notice.
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								There are helpers for the
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								[link math_toolkit.internals.series_evaluation evaluation of infinite series],
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								[link math_toolkit.internals.cf continued
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								fractions] and [link math_toolkit.roots.rational
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								rational approximations].
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								A [link math_toolkit.internals.minimax Remez algorithm implementation]
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								allows for the locating of minimax rational
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								approximations.
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								There are also (experimental) classes for the
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								[link math_toolkit.roots.polynomials manipulation of polynomials], for
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								[link math_toolkit.internals.error_test
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								testing a special function against tabulated test data], and for
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								the [link math_toolkit.internals.test_data
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								rapid generation of test data] and/or data for output to an
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								external graphing application.
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								[endsect] [/section:intro Introduction]
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								[/
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								  Copyright 2006, 2012, 2015 John Maddock and Paul A. Bristow.
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								  Distributed under the Boost Software License, Version 1.0.
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								  (See accompanying file LICENSE_1_0.txt or copy at
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								  http://www.boost.org/LICENSE_1_0.txt).
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								]
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