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additive_combine.hpp
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bernoulli_distribution.hpp
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beta_distribution.hpp
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binomial_distribution.hpp
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chi_squared_distribution.hpp
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discrete_distribution.hpp
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faure.hpp
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gamma_distribution.hpp
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geometric_distribution.hpp
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independent_bits.hpp
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niederreiter_base2.hpp
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non_central_chi_squared_distribution.hpp
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normal_distribution.hpp
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piecewise_constant_distribution.hpp
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random_device.hpp
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random_number_generator.hpp
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uniform_real.hpp
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/usr/include/boost/random/chi_squared_distribution.hpp
(6322B)
/* boost random/chi_squared_distribution.hpp header file * * Copyright Steven Watanabe 2011 * 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) * * See http://www.boost.org for most recent version including documentation. * * $Id$ */ #ifndef BOOST_RANDOM_CHI_SQUARED_DISTRIBUTION_HPP_INCLUDED #define BOOST_RANDOM_CHI_SQUARED_DISTRIBUTION_HPP_INCLUDED #include <iosfwd> #include <boost/limits.hpp> #include <boost/random/detail/config.hpp> #include <boost/random/gamma_distribution.hpp> namespace boost { namespace random { /** * The chi squared distribution is a real valued distribution with * one parameter, @c n. The distribution produces values > 0. * * The distribution function is * \f$\displaystyle P(x) = \frac{x^{(n/2)-1}e^{-x/2}}{\Gamma(n/2)2^{n/2}}\f$. */ template<class RealType = double> class chi_squared_distribution { public: typedef RealType result_type; typedef RealType input_type; class param_type { public: typedef chi_squared_distribution distribution_type; /** * Construct a param_type object. @c n * is the parameter of the distribution. * * Requires: t >=0 && 0 <= p <= 1 */ explicit param_type(RealType n_arg = RealType(1)) : _n(n_arg) {} /** Returns the @c n parameter of the distribution. */ RealType n() const { return _n; } #ifndef BOOST_RANDOM_NO_STREAM_OPERATORS /** Writes the parameters of the distribution to a @c std::ostream. */ template<class CharT, class Traits> friend std::basic_ostream<CharT,Traits>& operator<<(std::basic_ostream<CharT,Traits>& os, const param_type& parm) { os << parm._n; return os; } /** Reads the parameters of the distribution from a @c std::istream. */ template<class CharT, class Traits> friend std::basic_istream<CharT,Traits>& operator>>(std::basic_istream<CharT,Traits>& is, param_type& parm) { is >> parm._n; return is; } #endif /** Returns true if the parameters have the same values. */ friend bool operator==(const param_type& lhs, const param_type& rhs) { return lhs._n == rhs._n; } /** Returns true if the parameters have different values. */ friend bool operator!=(const param_type& lhs, const param_type& rhs) { return !(lhs == rhs); } private: RealType _n; }; /** * Construct a @c chi_squared_distribution object. @c n * is the parameter of the distribution. * * Requires: t >=0 && 0 <= p <= 1 */ explicit chi_squared_distribution(RealType n_arg = RealType(1)) : _impl(static_cast<RealType>(n_arg / 2)) { } /** * Construct an @c chi_squared_distribution object from the * parameters. */ explicit chi_squared_distribution(const param_type& parm) : _impl(static_cast<RealType>(parm.n() / 2)) { } /** * Returns a random variate distributed according to the * chi squared distribution. */ template<class URNG> RealType operator()(URNG& urng) { return 2 * _impl(urng); } /** * Returns a random variate distributed according to the * chi squared distribution with parameters specified by @c param. */ template<class URNG> RealType operator()(URNG& urng, const param_type& parm) const { return chi_squared_distribution(parm)(urng); } /** Returns the @c n parameter of the distribution. */ RealType n() const { return 2 * _impl.alpha(); } /** Returns the smallest value that the distribution can produce. */ RealType min BOOST_PREVENT_MACRO_SUBSTITUTION() const { return 0; } /** Returns the largest value that the distribution can produce. */ RealType max BOOST_PREVENT_MACRO_SUBSTITUTION() const { return (std::numeric_limits<RealType>::infinity)(); } /** Returns the parameters of the distribution. */ param_type param() const { return param_type(n()); } /** Sets parameters of the distribution. */ void param(const param_type& parm) { typedef gamma_distribution<RealType> impl_type; typename impl_type::param_type impl_parm(static_cast<RealType>(parm.n() / 2)); _impl.param(impl_parm); } /** * Effects: Subsequent uses of the distribution do not depend * on values produced by any engine prior to invoking reset. */ void reset() { _impl.reset(); } #ifndef BOOST_RANDOM_NO_STREAM_OPERATORS /** Writes the parameters of the distribution to a @c std::ostream. */ template<class CharT, class Traits> friend std::basic_ostream<CharT,Traits>& operator<<(std::basic_ostream<CharT,Traits>& os, const chi_squared_distribution& c2d) { os << c2d.param(); return os; } /** Reads the parameters of the distribution from a @c std::istream. */ template<class CharT, class Traits> friend std::basic_istream<CharT,Traits>& operator>>(std::basic_istream<CharT,Traits>& is, chi_squared_distribution& c2d) { c2d.read(is); return is; } #endif /** Returns true if the two distributions will produce the same sequence of values, given equal generators. */ friend bool operator==(const chi_squared_distribution& lhs, const chi_squared_distribution& rhs) { return lhs._impl == rhs._impl; } /** Returns true if the two distributions could produce different sequences of values, given equal generators. */ friend bool operator!=(const chi_squared_distribution& lhs, const chi_squared_distribution& rhs) { return !(lhs == rhs); } private: /// @cond show_private template<class CharT, class Traits> void read(std::basic_istream<CharT, Traits>& is) { param_type parm; if(is >> parm) { param(parm); } } gamma_distribution<RealType> _impl; /// @endcond }; } } #endif
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