chi_squared_distribution.hpp

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//============================================================================
// MCKL/include/mckl/random/chi_squared_distribution.hpp
//----------------------------------------------------------------------------
// MCKL: Monte Carlo Kernel Library
//----------------------------------------------------------------------------
// Copyright (c) 2013-2018, Yan Zhou
// All rights reserved.
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//============================================================================

#ifndef MCKL_RANDOM_CHI_SQUARED_DISTRIBUTION_HPP
#define MCKL_RANDOM_CHI_SQUARED_DISTRIBUTION_HPP

#include <mckl/random/internal/common.hpp>
#include <mckl/random/gamma_distribution.hpp>

namespace mckl {

namespace internal {

template <typename RealType>
inline bool chi_squared_distribution_check_param(RealType n)
{
    return n > 0;
}

} // namespace internal

template <typename RealType, typename RNGType>
inline void chi_squared_distribution(
    RNGType &rng, std::size_t n, RealType *r, RealType df)
{
    gamma_distribution(rng, n, r, df / 2, static_cast<RealType>(2));
}

template <typename RealType, typename RNGType>
inline void chi_squared_distribution(RNGType &rng, std::size_t n, RealType *r,
    const typename ChiSquaredDistribution<RealType>::param_type &param)
{
    chi_squared_distribution(rng, n, r, param.n());
}

template <typename RealType>
class ChiSquaredDistribution
{
    MCKL_DEFINE_RANDOM_DISTRIBUTION_ASSERT_REAL_TYPE(ChiSquared)
    MCKL_DEFINE_RANDOM_DISTRIBUTION_1(
        ChiSquared, chi_squared, RealType, result_type, n, 1)
    MCKL_DEFINE_RANDOM_DISTRIBUTION_MEMBER_1(
        GammaDistribution<RealType>, gamma_)

  public:
    result_type min() const { return 0; }

    result_type max() const { return std::numeric_limits<result_type>::max(); }

    void reset() { gamma_ = GammaDistribution<RealType>(n() / 2, 2); }

  private:
    template <typename RNGType>
    result_type generate(RNGType &rng, const param_type &param)
    {
        if (param == param_) {
            return gamma_(rng);
        }

        GammaDistribution<RealType> gamma(param.n() / 2, 2);

        return gamma(rng);
    }
}; // class ChiSquaredDistribution

MCKL_DEFINE_RANDOM_DISTRIBUTION_RAND(ChiSquared, RealType)

} // namespace mckl

#endif // MCKL_RANDOM_CHI_SQUARED_DISTRIBUTION_HPP