boost/math/distributions/inverse_chi_squared.hpp
// Copyright John Maddock 2010.
// Copyright Paul A. Bristow 2010.
// 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_INVERSE_CHI_SQUARED_HPP
#define BOOST_MATH_DISTRIBUTIONS_INVERSE_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> // for complements.
#include <boost/math/distributions/detail/common_error_handling.hpp> // for error checks.
#include <boost/math/special_functions/fpclassify.hpp> // for isfinite
// See http://en.wikipedia.org/wiki/Scaled-inverse-chi-square_distribution
// for definitions of this scaled version.
// See http://en.wikipedia.org/wiki/Inverse-chi-square_distribution
// for unscaled version.
// http://reference.wolfram.com/mathematica/ref/InverseChiSquareDistribution.html
// Weisstein, Eric W. "Inverse Chi-Squared Distribution." From MathWorld--A Wolfram Web Resource.
// http://mathworld.wolfram.com/InverseChi-SquaredDistribution.html
#include <utility>
namespace boost{ namespace math{
namespace detail
{
template <class RealType, class Policy>
inline bool check_inverse_chi_squared( // Check both distribution parameters.
const char* function,
RealType degrees_of_freedom, // degrees_of_freedom (aka nu).
RealType scale, // scale (aka sigma^2)
RealType* result,
const Policy& pol)
{
return check_scale(function, scale, result, pol)
&& check_df(function, degrees_of_freedom,
result, pol);
} // bool check_inverse_chi_squared
} // namespace detail
template <class RealType = double, class Policy = policies::policy<> >
class inverse_chi_squared_distribution
{
public:
typedef RealType value_type;
typedef Policy policy_type;
inverse_chi_squared_distribution(RealType df, RealType l_scale) : m_df(df), m_scale (l_scale)
{
RealType result;
detail::check_df(
"boost::math::inverse_chi_squared_distribution<%1%>::inverse_chi_squared_distribution",
m_df, &result, Policy())
&& detail::check_scale(
"boost::math::inverse_chi_squared_distribution<%1%>::inverse_chi_squared_distribution",
m_scale, &result, Policy());
} // inverse_chi_squared_distribution constructor
inverse_chi_squared_distribution(RealType df = 1) : m_df(df)
{
RealType result;
m_scale = 1 / m_df ; // Default scale = 1 / degrees of freedom (Wikipedia definition 1).
detail::check_df(
"boost::math::inverse_chi_squared_distribution<%1%>::inverse_chi_squared_distribution",
m_df, &result, Policy());
} // inverse_chi_squared_distribution
RealType degrees_of_freedom()const
{
return m_df; // aka nu
}
RealType scale()const
{
return m_scale; // aka xi
}
// Parameter estimation: NOT implemented yet.
//static RealType find_degrees_of_freedom(
// RealType difference_from_variance,
// RealType alpha,
// RealType beta,
// RealType variance,
// RealType hint = 100);
private:
// Data members:
RealType m_df; // degrees of freedom are treated as a real number.
RealType m_scale; // distribution scale.
}; // class chi_squared_distribution
typedef inverse_chi_squared_distribution<double> inverse_chi_squared;
#ifdef __cpp_deduction_guides
template <class RealType>
inverse_chi_squared_distribution(RealType)->inverse_chi_squared_distribution<typename boost::math::tools::promote_args<RealType>::type>;
template <class RealType>
inverse_chi_squared_distribution(RealType,RealType)->inverse_chi_squared_distribution<typename boost::math::tools::promote_args<RealType>::type>;
#endif
template <class RealType, class Policy>
inline const std::pair<RealType, RealType> range(const inverse_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>(static_cast<RealType>(0), max_value<RealType>()); // 0 to + infinity.
}
template <class RealType, class Policy>
inline const std::pair<RealType, RealType> support(const inverse_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>(static_cast<RealType>(0), tools::max_value<RealType>()); // 0 to + infinity.
}
template <class RealType, class Policy>
RealType pdf(const inverse_chi_squared_distribution<RealType, Policy>& dist, const RealType& x)
{
BOOST_MATH_STD_USING // for ADL of std functions.
RealType df = dist.degrees_of_freedom();
RealType scale = dist.scale();
RealType error_result;
static const char* function = "boost::math::pdf(const inverse_chi_squared_distribution<%1%>&, %1%)";
if(false == detail::check_inverse_chi_squared
(function, df, scale, &error_result, Policy())
)
{ // Bad distribution.
return error_result;
}
if((x < 0) || !(boost::math::isfinite)(x))
{ // Bad x.
return policies::raise_domain_error<RealType>(
function, "inverse Chi Square parameter was %1%, but must be >= 0 !", x, Policy());
}
if(x == 0)
{ // Treat as special case.
return 0;
}
// Wikipedia scaled inverse chi sq (df, scale) related to inv gamma (df/2, df * scale /2)
// so use inverse gamma pdf with shape = df/2, scale df * scale /2
// RealType shape = df /2; // inv_gamma shape
// RealType scale = df * scale/2; // inv_gamma scale
// RealType result = gamma_p_derivative(shape, scale / x, Policy()) * scale / (x * x);
RealType result = df * scale/2 / x;
if(result < tools::min_value<RealType>())
return 0; // Random variable is near enough infinite.
result = gamma_p_derivative(df/2, result, Policy()) * df * scale/2;
if(result != 0) // prevent 0 / 0, gamma_p_derivative -> 0 faster than x^2
result /= (x * x);
return result;
} // pdf
template <class RealType, class Policy>
inline RealType cdf(const inverse_chi_squared_distribution<RealType, Policy>& dist, const RealType& x)
{
static const char* function = "boost::math::cdf(const inverse_chi_squared_distribution<%1%>&, %1%)";
RealType df = dist.degrees_of_freedom();
RealType scale = dist.scale();
RealType error_result;
if(false ==
detail::check_inverse_chi_squared(function, df, scale, &error_result, Policy())
)
{ // Bad distribution.
return error_result;
}
if((x < 0) || !(boost::math::isfinite)(x))
{ // Bad x.
return policies::raise_domain_error<RealType>(
function, "inverse Chi Square parameter was %1%, but must be >= 0 !", x, Policy());
}
if (x == 0)
{ // Treat zero as a special case.
return 0;
}
// RealType shape = df /2; // inv_gamma shape,
// RealType scale = df * scale/2; // inv_gamma scale,
// result = boost::math::gamma_q(shape, scale / x, Policy()); // inverse_gamma code.
return boost::math::gamma_q(df / 2, (df * (scale / 2)) / x, Policy());
} // cdf
template <class RealType, class Policy>
inline RealType quantile(const inverse_chi_squared_distribution<RealType, Policy>& dist, const RealType& p)
{
using boost::math::gamma_q_inv;
RealType df = dist.degrees_of_freedom();
RealType scale = dist.scale();
static const char* function = "boost::math::quantile(const inverse_chi_squared_distribution<%1%>&, %1%)";
// Error check:
RealType error_result;
if(false == detail::check_df(
function, df, &error_result, Policy())
&& detail::check_probability(
function, p, &error_result, Policy()))
{
return error_result;
}
if(false == detail::check_probability(
function, p, &error_result, Policy()))
{
return error_result;
}
// RealType shape = df /2; // inv_gamma shape,
// RealType scale = df * scale/2; // inv_gamma scale,
// result = scale / gamma_q_inv(shape, p, Policy());
RealType result = gamma_q_inv(df /2, p, Policy());
if(result == 0)
return policies::raise_overflow_error<RealType, Policy>(function, "Random variable is infinite.", Policy());
result = df * (scale / 2) / result;
return result;
} // quantile
template <class RealType, class Policy>
inline RealType cdf(const complemented2_type<inverse_chi_squared_distribution<RealType, Policy>, RealType>& c)
{
using boost::math::gamma_q_inv;
RealType const& df = c.dist.degrees_of_freedom();
RealType const& scale = c.dist.scale();
RealType const& x = c.param;
static const char* function = "boost::math::cdf(const inverse_chi_squared_distribution<%1%>&, %1%)";
// Error check:
RealType error_result;
if(false == detail::check_df(
function, df, &error_result, Policy()))
{
return error_result;
}
if (x == 0)
{ // Treat zero as a special case.
return 1;
}
if((x < 0) || !(boost::math::isfinite)(x))
{
return policies::raise_domain_error<RealType>(
function, "inverse Chi Square parameter was %1%, but must be > 0 !", x, Policy());
}
// RealType shape = df /2; // inv_gamma shape,
// RealType scale = df * scale/2; // inv_gamma scale,
// result = gamma_p(shape, scale/c.param, Policy()); use inv_gamma.
return gamma_p(df / 2, (df * scale/2) / x, Policy()); // OK
} // cdf(complemented
template <class RealType, class Policy>
inline RealType quantile(const complemented2_type<inverse_chi_squared_distribution<RealType, Policy>, RealType>& c)
{
using boost::math::gamma_q_inv;
RealType const& df = c.dist.degrees_of_freedom();
RealType const& scale = c.dist.scale();
RealType const& q = c.param;
static const char* function = "boost::math::quantile(const inverse_chi_squared_distribution<%1%>&, %1%)";
// Error check:
RealType error_result;
if(false == detail::check_df(function, df, &error_result, Policy()))
{
return error_result;
}
if(false == detail::check_probability(function, q, &error_result, Policy()))
{
return error_result;
}
// RealType shape = df /2; // inv_gamma shape,
// RealType scale = df * scale/2; // inv_gamma scale,
// result = scale / gamma_p_inv(shape, q, Policy()); // using inv_gamma.
RealType result = gamma_p_inv(df/2, q, Policy());
if(result == 0)
return policies::raise_overflow_error<RealType, Policy>(function, "Random variable is infinite.", Policy());
result = (df * scale / 2) / result;
return result;
} // quantile(const complement
template <class RealType, class Policy>
inline RealType mean(const inverse_chi_squared_distribution<RealType, Policy>& dist)
{ // Mean of inverse Chi-Squared distribution.
RealType df = dist.degrees_of_freedom();
RealType scale = dist.scale();
static const char* function = "boost::math::mean(const inverse_chi_squared_distribution<%1%>&)";
if(df <= 2)
return policies::raise_domain_error<RealType>(
function,
"inverse Chi-Squared distribution only has a mode for degrees of freedom > 2, but got degrees of freedom = %1%.",
df, Policy());
return (df * scale) / (df - 2);
} // mean
template <class RealType, class Policy>
inline RealType variance(const inverse_chi_squared_distribution<RealType, Policy>& dist)
{ // Variance of inverse Chi-Squared distribution.
RealType df = dist.degrees_of_freedom();
RealType scale = dist.scale();
static const char* function = "boost::math::variance(const inverse_chi_squared_distribution<%1%>&)";
if(df <= 4)
{
return policies::raise_domain_error<RealType>(
function,
"inverse Chi-Squared distribution only has a variance for degrees of freedom > 4, but got degrees of freedom = %1%.",
df, Policy());
}
return 2 * df * df * scale * scale / ((df - 2)*(df - 2) * (df - 4));
} // variance
template <class RealType, class Policy>
inline RealType mode(const inverse_chi_squared_distribution<RealType, Policy>& dist)
{ // mode is not defined in Mathematica.
// See Discussion section http://en.wikipedia.org/wiki/Talk:Scaled-inverse-chi-square_distribution
// for origin of the formula used below.
RealType df = dist.degrees_of_freedom();
RealType scale = dist.scale();
static const char* function = "boost::math::mode(const inverse_chi_squared_distribution<%1%>&)";
if(df < 0)
return policies::raise_domain_error<RealType>(
function,
"inverse Chi-Squared distribution only has a mode for degrees of freedom >= 0, but got degrees of freedom = %1%.",
df, Policy());
return (df * scale) / (df + 2);
}
//template <class RealType, class Policy>
//inline RealType median(const inverse_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 inverse_Chi-Squared distribution only has a median for degrees of freedom >= 0, but got degrees of freedom = %1%.",
// df);
// return df;
//}
// Now implemented via quantile(half) in derived accessors.
template <class RealType, class Policy>
inline RealType skewness(const inverse_chi_squared_distribution<RealType, Policy>& dist)
{
BOOST_MATH_STD_USING // For ADL
RealType df = dist.degrees_of_freedom();
static const char* function = "boost::math::skewness(const inverse_chi_squared_distribution<%1%>&)";
if(df <= 6)
return policies::raise_domain_error<RealType>(
function,
"inverse Chi-Squared distribution only has a skewness for degrees of freedom > 6, but got degrees of freedom = %1%.",
df, Policy());
return 4 * sqrt (2 * (df - 4)) / (df - 6); // Not a function of scale.
}
template <class RealType, class Policy>
inline RealType kurtosis(const inverse_chi_squared_distribution<RealType, Policy>& dist)
{
RealType df = dist.degrees_of_freedom();
static const char* function = "boost::math::kurtosis(const inverse_chi_squared_distribution<%1%>&)";
if(df <= 8)
return policies::raise_domain_error<RealType>(
function,
"inverse Chi-Squared distribution only has a kurtosis for degrees of freedom > 8, but got degrees of freedom = %1%.",
df, Policy());
return kurtosis_excess(dist) + 3;
}
template <class RealType, class Policy>
inline RealType kurtosis_excess(const inverse_chi_squared_distribution<RealType, Policy>& dist)
{
RealType df = dist.degrees_of_freedom();
static const char* function = "boost::math::kurtosis(const inverse_chi_squared_distribution<%1%>&)";
if(df <= 8)
return policies::raise_domain_error<RealType>(
function,
"inverse Chi-Squared distribution only has a kurtosis excess for degrees of freedom > 8, but got degrees of freedom = %1%.",
df, Policy());
return 12 * (5 * df - 22) / ((df - 6 )*(df - 8)); // Not a function of scale.
}
//
// Parameter estimation comes last:
//
} // 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_INVERSE_CHI_SQUARED_HPP