chi_squared.hpp

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// Copyright John Maddock 2006, 2007.// Copyright Paul A. Bristow 2008.// 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)#ifndef BOOST_MATH_DISTRIBUTIONS_CHI_SQUARED_HPP#define BOOST_MATH_DISTRIBUTIONS_CHI_SQUARED_HPP#include <boost/math/distributions/fwd.hpp>#include <boost/math/special_functions/gamma.hpp> // for incomplete beta.#include <boost/math/distributions/complement.hpp> // complements#include <boost/math/distributions/detail/common_error_handling.hpp> // error checks#include <boost/math/special_functions/fpclassify.hpp>#include <utility>namespace boost{ namespace math{template <class RealType = double, class Policy = policies::policy<> >class chi_squared_distribution{public:   typedef RealType value_type;   typedef Policy policy_type;   chi_squared_distribution(RealType i) : m_df(i)   {      RealType result;      detail::check_df(         "boost::math::chi_squared_distribution<%1%>::chi_squared_distribution", m_df, &result, Policy());   } // chi_squared_distribution   RealType degrees_of_freedom()const   {      return m_df;   }   // Parameter estimation:   static RealType find_degrees_of_freedom(      RealType difference_from_variance,      RealType alpha,      RealType beta,      RealType variance,      RealType hint = 100);private:   //   // Data member:   //   RealType m_df;  // degrees of freedom are a real number.}; // class chi_squared_distributiontypedef chi_squared_distribution<double> chi_squared;template <class RealType, class Policy>inline const std::pair<RealType, RealType> range(const chi_squared_distribution<RealType, Policy>& /*dist*/){ // Range of permissible values for random variable x.   using boost::math::tools::max_value;   return std::pair<RealType, RealType>(0, max_value<RealType>()); // 0 to + infinity.}template <class RealType, class Policy>inline const std::pair<RealType, RealType> support(const chi_squared_distribution<RealType, Policy>& /*dist*/){ // Range of supported values for random variable x.   // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.   return std::pair<RealType, RealType>(0, tools::max_value<RealType>()); // 0 to + infinity.}template <class RealType, class Policy>RealType pdf(const chi_squared_distribution<RealType, Policy>& dist, const RealType& chi_square){   BOOST_MATH_STD_USING  // for ADL of std functions   RealType degrees_of_freedom = dist.degrees_of_freedom();   // Error check:   RealType error_result;   static const char* function = "boost::math::pdf(const chi_squared_distribution<%1%>&, %1%)";   if(false == detail::check_df(         function, degrees_of_freedom, &error_result, Policy()))      return error_result;   if((chi_square < 0) || !(boost::math::isfinite)(chi_square))   {      return policies::raise_domain_error<RealType>(         function, "Chi Square parameter was %1%, but must be > 0 !", chi_square, Policy());   }   if(chi_square == 0)   {      // Handle special cases:      if(degrees_of_freedom < 2)      {         return policies::raise_overflow_error<RealType>(            function, 0, Policy());      }      else if(degrees_of_freedom == 2)      {         return 0.5f;      }      else      {         return 0;      }   }   return gamma_p_derivative(degrees_of_freedom / 2, chi_square / 2, Policy()) / 2;} // pdftemplate <class RealType, class Policy>inline RealType cdf(const chi_squared_distribution<RealType, Policy>& dist, const RealType& chi_square){   RealType degrees_of_freedom = dist.degrees_of_freedom();   // Error check:   RealType error_result;   static const char* function = "boost::math::cdf(const chi_squared_distribution<%1%>&, %1%)";   if(false == detail::check_df(         function, degrees_of_freedom, &error_result, Policy()))      return error_result;   if((chi_square < 0) || !(boost::math::isfinite)(chi_square))   {      return policies::raise_domain_error<RealType>(         function, "Chi Square parameter was %1%, but must be > 0 !", chi_square, Policy());   }   return boost::math::gamma_p(degrees_of_freedom / 2, chi_square / 2, Policy());} // cdftemplate <class RealType, class Policy>inline RealType quantile(const chi_squared_distribution<RealType, Policy>& dist, const RealType& p){   RealType degrees_of_freedom = dist.degrees_of_freedom();   static const char* function = "boost::math::quantile(const chi_squared_distribution<%1%>&, %1%)";   // Error check:   RealType error_result;   if(false == detail::check_df(         function, degrees_of_freedom, &error_result, Policy())         && detail::check_probability(            function, p, &error_result, Policy()))      return error_result;   return 2 * boost::math::gamma_p_inv(degrees_of_freedom / 2, p, Policy());} // quantiletemplate <class RealType, class Policy>inline RealType cdf(const complemented2_type<chi_squared_distribution<RealType, Policy>, RealType>& c){   RealType const& degrees_of_freedom = c.dist.degrees_of_freedom();   RealType const& chi_square = c.param;   static const char* function = "boost::math::cdf(const chi_squared_distribution<%1%>&, %1%)";   // Error check:   RealType error_result;   if(false == detail::check_df(         function, degrees_of_freedom, &error_result, Policy()))      return error_result;   if((chi_square < 0) || !(boost::math::isfinite)(chi_square))   {      return policies::raise_domain_error<RealType>(         function, "Chi Square parameter was %1%, but must be > 0 !", chi_square, Policy());   }   return boost::math::gamma_q(degrees_of_freedom / 2, chi_square / 2, Policy());}template <class RealType, class Policy>inline RealType quantile(const complemented2_type<chi_squared_distribution<RealType, Policy>, RealType>& c){   RealType const& degrees_of_freedom = c.dist.degrees_of_freedom();   RealType const& q = c.param;   static const char* function = "boost::math::quantile(const chi_squared_distribution<%1%>&, %1%)";   // Error check:   RealType error_result;   if(false == detail::check_df(         function, degrees_of_freedom, &error_result, Policy())         && detail::check_probability(            function, q, &error_result, Policy()))      return error_result;   return 2 * boost::math::gamma_q_inv(degrees_of_freedom / 2, q, Policy());}template <class RealType, class Policy>inline RealType mean(const chi_squared_distribution<RealType, Policy>& dist){ // Mean of Chi-Squared distribution = v.  return dist.degrees_of_freedom();} // meantemplate <class RealType, class Policy>inline RealType variance(const chi_squared_distribution<RealType, Policy>& dist){ // Variance of Chi-Squared distribution = 2v.  return 2 * dist.degrees_of_freedom();} // variancetemplate <class RealType, class Policy>inline RealType mode(const chi_squared_distribution<RealType, Policy>& dist){   RealType df = dist.degrees_of_freedom();   static const char* function = "boost::math::mode(const chi_squared_distribution<%1%>&)";   // Most sources only define mode for df >= 2,   // but for 0 <= df <= 2, the pdf maximum actually occurs at random variate = 0;   // So one could extend the definition of mode thus:   //if(df < 0)   //{   //   return policies::raise_domain_error<RealType>(   //      function,   //      "Chi-Squared distribution only has a mode for degrees of freedom >= 0, but got degrees of freedom = %1%.",   //      df, Policy());   //}   //return (df <= 2) ? 0 : df - 2;   if(df < 2)      return policies::raise_domain_error<RealType>(         function,         "Chi-Squared distribution only has a mode for degrees of freedom >= 2, but got degrees of freedom = %1%.",         df, Policy());   return df - 2;}//template <class RealType, class Policy>//inline RealType median(const chi_squared_distribution<RealType, Policy>& dist)//{ // Median is given by Quantile[dist, 1/2]//   RealType df = dist.degrees_of_freedom();//   if(df <= 1)//      return tools::domain_error<RealType>(//         BOOST_CURRENT_FUNCTION,//         "The Chi-Squared distribution only has a mode for degrees of freedom >= 2, but got degrees of freedom = %1%.",//         df);//   return df - RealType(2)/3;//}// Now implemented via quantile(half) in derived accessors.template <class RealType, class Policy>inline RealType skewness(const chi_squared_distribution<RealType, Policy>& dist){   BOOST_MATH_STD_USING // For ADL   RealType df = dist.degrees_of_freedom();   return sqrt (8 / df);  // == 2 * sqrt(2 / df);}template <class RealType, class Policy>inline RealType kurtosis(const chi_squared_distribution<RealType, Policy>& dist){   RealType df = dist.degrees_of_freedom();   return 3 + 12 / df;}template <class RealType, class Policy>inline RealType kurtosis_excess(const chi_squared_distribution<RealType, Policy>& dist){   RealType df = dist.degrees_of_freedom();   return 12 / df;}//// Parameter estimation comes last://namespace detail{template <class RealType, class Policy>struct df_estimator{   df_estimator(RealType a, RealType b, RealType variance, RealType delta)      : alpha(a), beta(b), ratio(delta/variance) {}   RealType operator()(const RealType& df)   {      if(df <= tools::min_value<RealType>())         return 1;      chi_squared_distribution<RealType, Policy> cs(df);      RealType result;      if(ratio > 0)      {         RealType r = 1 + ratio;         result = cdf(cs, quantile(complement(cs, alpha)) / r) - beta;      }      else      {         RealType r = 1 + ratio;         result = cdf(complement(cs, quantile(cs, alpha) / r)) - beta;      }      return result;   }private:   RealType alpha, beta, ratio;};} // namespace detailtemplate <class RealType, class Policy>RealType chi_squared_distribution<RealType, Policy>::find_degrees_of_freedom(   RealType difference_from_variance,   RealType alpha,   RealType beta,   RealType variance,   RealType hint){   static const char* function = "boost::math::chi_squared_distribution<%1%>::find_degrees_of_freedom(%1%,%1%,%1%,%1%,%1%)";   // Check for domain errors:   RealType error_result;   if(false == detail::check_probability(         function, alpha, &error_result, Policy())         && detail::check_probability(function, beta, &error_result, Policy()))      return error_result;   if(hint <= 0)      hint = 1;   detail::df_estimator<RealType, Policy> f(alpha, beta, variance, difference_from_variance);   tools::eps_tolerance<RealType> tol(policies::digits<RealType, Policy>());   boost::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();   std::pair<RealType, RealType> r = tools::bracket_and_solve_root(f, hint, RealType(2), false, tol, max_iter, Policy());   RealType result = r.first + (r.second - r.first) / 2;   if(max_iter >= policies::get_max_root_iterations<Policy>())   {      policies::raise_evaluation_error<RealType>(function, "Unable to locate solution in a reasonable time:"         " either there is no answer to how many degrees of freedom are required"         " or the answer is infinite.  Current best guess is %1%", result, Policy());   }   return result;}} // namespace math} // namespace boost// This include must be at the end, *after* the accessors// for this distribution have been defined, in order to// keep compilers that support two-phase lookup happy.#include <boost/math/distributions/detail/derived_accessors.hpp>#endif // BOOST_MATH_DISTRIBUTIONS_CHI_SQUARED_HPP

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