fisher_f_distribution.hpp

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//============================================================================
// vSMC/include/vsmc/rng/fisher_f_distribution.hpp
//----------------------------------------------------------------------------
//                         vSMC: Scalable Monte Carlo
//----------------------------------------------------------------------------
// Copyright (c) 2013-2015, Yan Zhou
// All rights reserved.
//
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// modification, are permitted provided that the following conditions are met:
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//   this list of conditions and the following disclaimer.
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//   this list of conditions and the following disclaimer in the documentation
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//============================================================================

#ifndef VSMC_RNG_FISHER_F_DISTRIBUTION_HPP
#define VSMC_RNG_FISHER_F_DISTRIBUTION_HPP

#include <vsmc/rng/internal/common.hpp>
#include <vsmc/rng/chi_squared_distribution.hpp>

namespace vsmc
{

namespace internal
{

template <typename RealType>
inline bool fisher_f_distribution_check_param(RealType m, RealType n)
{
    return m > 0 && n > 0;
}

} // namespace vsmc::internal

template <typename RealType>
class FisherFDistribution
{
    VSMC_DEFINE_RNG_DISTRIBUTION_2(
        FisherF, fisher_f, RealType, result_type, m, 1, result_type, n, 1)
    VSMC_DEFINE_RNG_DISTRIBUTION_OPERATORS

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

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

    void reset()
    {
        chi_squared_m_ = ChiSquaredDistribution<RealType>(m());
        chi_squared_n_ = ChiSquaredDistribution<RealType>(n());
    }

    private:
    ChiSquaredDistribution<RealType> chi_squared_m_;
    ChiSquaredDistribution<RealType> chi_squared_n_;

    template <typename RNGType>
    result_type generate(RNGType &rng, const param_type &param)
    {
        if (param == param_)
            return (chi_squared_m_(rng) / m()) / (chi_squared_n_(rng) / n());

        ChiSquaredDistribution<RealType> chi_squared_m(param.m());
        ChiSquaredDistribution<RealType> chi_squared_n(param.n());

        return (chi_squared_m(rng) / param.m()) /
            (chi_squared_n(rng) / param.n());
    }
}; // class FisherFDistribution

namespace internal
{

template <std::size_t K, typename RealType, typename RNGType>
inline void fisher_f_distribution_impl(
    RNGType &rng, std::size_t n, RealType *r, RealType df1, RealType df2)
{
    RealType s[K];
    chi_squared_distribution(rng, n, s, df1);
    chi_squared_distribution(rng, n, r, df2);
    mul(n, 1 / df1, s, s);
    mul(n, 1 / df2, r, r);
    div(n, s, r, r);
}

} // namespace vsmc::internal

template <typename RealType, typename RNGType>
inline void fisher_f_distribution(
    RNGType &rng, std::size_t n, RealType *r, RealType df1, RealType df2)
{
    const std::size_t k = 1000;
    const std::size_t m = n / k;
    const std::size_t l = n % k;
    for (std::size_t i = 0; i != m; ++i)
        internal::fisher_f_distribution_impl<k>(rng, k, r + i * k, df1, df2);
    internal::fisher_f_distribution_impl<k>(rng, l, r + m * k, df1, df2);
}

template <typename RealType, typename RNGType>
inline void rng_rand(RNGType &rng, FisherFDistribution<RealType> &dist,
    std::size_t n, RealType *r)
{
    dist(rng, n, r);
}

} // namespace vsmc

#endif // VSMC_RNG_FISHER_F_DISTRIBUTION_HPP