# GL Profile Suite / boost_1_51_0 / boost / random / student_t_distribution.hpp

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 /* boost random/student_t_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. * * $Id: student_t_distribution.hpp 71018 2011-04-05 21:27:52Z steven_watanabe$ */ #ifndef BOOST_RANDOM_STUDENT_T_DISTRIBUTION_HPP #define BOOST_RANDOM_STUDENT_T_DISTRIBUTION_HPP #include #include #include #include #include #include #include namespace boost { namespace random { /** * The Student t distribution is a real valued distribution with one * parameter n, the number of degrees of freedom. * * It has \f$\displaystyle p(x) = * \frac{1}{\sqrt{n\pi}} * \frac{\Gamma((n+1)/2)}{\Gamma(n/2)} * \left(1+\frac{x^2}{n}\right)^{-(n+1)/2} * \f$. */ template class student_t_distribution { public: typedef RealType result_type; typedef RealType input_type; class param_type { public: typedef student_t_distribution distribution_type; /** * Constructs a @c param_type with "n" degrees of freedom. * * Requires: n > 0 */ explicit param_type(RealType n_arg = RealType(1.0)) : _n(n_arg) {} /** Returns the number of degrees of freedom of the distribution. */ RealType n() const { return _n; } /** Writes a @c param_type to a @c std::ostream. */ BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm) { os << parm._n; return os; } /** Reads a @c param_type from a @c std::istream. */ BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm) { is >> parm._n; return is; } /** Returns true if the two sets of parameters are the same. */ BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs) { return lhs._n == rhs._n; } /** Returns true if the two sets of parameters are the different. */ BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type) private: RealType _n; }; /** * Constructs an @c student_t_distribution with "n" degrees of freedom. * * Requires: n > 0 */ explicit student_t_distribution(RealType n_arg = RealType(1.0)) : _normal(), _chi_squared(n_arg) {} /** Constructs an @c student_t_distribution from its parameters. */ explicit student_t_distribution(const param_type& parm) : _normal(), _chi_squared(parm.n()) {} /** * Returns a random variate distributed according to the * Student t distribution. */ template RealType operator()(URNG& urng) { using std::sqrt; return _normal(urng) / sqrt(_chi_squared(urng) / n()); } /** * Returns a random variate distributed accordint to the Student * t distribution with parameters specified by @c param. */ template RealType operator()(URNG& urng, const param_type& parm) const { return student_t_distribution(parm)(urng); } /** Returns the number of degrees of freedom. */ RealType n() const { return _chi_squared.n(); } /** Returns the smallest value that the distribution can produce. */ RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const { return -std::numeric_limits::infinity(); } /** Returns the largest value that the distribution can produce. */ RealType max BOOST_PREVENT_MACRO_SUBSTITUTION () const { return std::numeric_limits::infinity(); } /** Returns the parameters of the distribution. */ param_type param() const { return param_type(n()); } /** Sets the parameters of the distribution. */ void param(const param_type& parm) { typedef chi_squared_distribution chi_squared_type; typename chi_squared_type::param_type chi_squared_param(parm.n()); _chi_squared.param(chi_squared_param); } /** * Effects: Subsequent uses of the distribution do not depend * on values produced by any engine prior to invoking reset. */ void reset() { _normal.reset(); _chi_squared.reset(); } /** Writes a @c student_t_distribution to a @c std::ostream. */ BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, student_t_distribution, td) { os << td.param(); return os; } /** Reads a @c student_t_distribution from a @c std::istream. */ BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, student_t_distribution, td) { param_type parm; if(is >> parm) { td.param(parm); } return is; } /** * Returns true if the two instances of @c student_t_distribution will * return identical sequences of values given equal generators. */ BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(student_t_distribution, lhs, rhs) { return lhs._normal == rhs._normal && lhs._chi_squared == rhs._chi_squared; } /** * Returns true if the two instances of @c student_t_distribution will * return different sequences of values given equal generators. */ BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(student_t_distribution) private: normal_distribution _normal; chi_squared_distribution _chi_squared; }; } // namespace random } // namespace boost #endif // BOOST_RANDOM_STUDENT_T_DISTRIBUTION_HPP