1 /* boost random/student_t_distribution.hpp header file 2 * 3 * Copyright Steven Watanabe 2011 4 * Distributed under the Boost Software License, Version 1.0. (See 5 * accompanying file LICENSE_1_0.txt or copy at 6 * http://www.boost.org/LICENSE_1_0.txt) 7 * 8 * See http://www.boost.org for most recent version including documentation. 9 * 10 * $Id$ 11 */ 12 13 #ifndef BOOST_RANDOM_STUDENT_T_DISTRIBUTION_HPP 14 #define BOOST_RANDOM_STUDENT_T_DISTRIBUTION_HPP 15 16 #include <boost/config/no_tr1/cmath.hpp> 17 #include <iosfwd> 18 #include <boost/config.hpp> 19 #include <boost/limits.hpp> 20 #include <boost/random/detail/operators.hpp> 21 #include <boost/random/chi_squared_distribution.hpp> 22 #include <boost/random/normal_distribution.hpp> 23 24 namespace boost { 25 namespace random { 26 27 /** 28 * The Student t distribution is a real valued distribution with one 29 * parameter n, the number of degrees of freedom. 30 * 31 * It has \f$\displaystyle p(x) = 32 * \frac{1}{\sqrt{n\pi}} 33 * \frac{\Gamma((n+1)/2)}{\Gamma(n/2)} 34 * \left(1+\frac{x^2}{n}\right)^{-(n+1)/2} 35 * \f$. 36 */ 37 template<class RealType = double> 38 class student_t_distribution { 39 public: 40 typedef RealType result_type; 41 typedef RealType input_type; 42 43 class param_type { 44 public: 45 typedef student_t_distribution distribution_type; 46 47 /** 48 * Constructs a @c param_type with "n" degrees of freedom. 49 * 50 * Requires: n > 0 51 */ param_type(RealType n_arg=RealType (1.0))52 explicit param_type(RealType n_arg = RealType(1.0)) 53 : _n(n_arg) 54 {} 55 56 /** Returns the number of degrees of freedom of the distribution. */ n() const57 RealType n() const { return _n; } 58 59 /** Writes a @c param_type to a @c std::ostream. */ BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os,param_type,parm)60 BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm) 61 { os << parm._n; return os; } 62 63 /** Reads a @c param_type from a @c std::istream. */ BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is,param_type,parm)64 BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm) 65 { is >> parm._n; return is; } 66 67 /** Returns true if the two sets of parameters are the same. */ BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type,lhs,rhs)68 BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs) 69 { return lhs._n == rhs._n; } 70 71 /** Returns true if the two sets of parameters are the different. */ 72 BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type) 73 74 private: 75 RealType _n; 76 }; 77 78 /** 79 * Constructs an @c student_t_distribution with "n" degrees of freedom. 80 * 81 * Requires: n > 0 82 */ student_t_distribution(RealType n_arg=RealType (1.0))83 explicit student_t_distribution(RealType n_arg = RealType(1.0)) 84 : _normal(), _chi_squared(n_arg) 85 {} 86 /** Constructs an @c student_t_distribution from its parameters. */ student_t_distribution(const param_type & parm)87 explicit student_t_distribution(const param_type& parm) 88 : _normal(), _chi_squared(parm.n()) 89 {} 90 91 /** 92 * Returns a random variate distributed according to the 93 * Student t distribution. 94 */ 95 template<class URNG> operator ()(URNG & urng)96 RealType operator()(URNG& urng) 97 { 98 using std::sqrt; 99 return _normal(urng) / sqrt(_chi_squared(urng) / n()); 100 } 101 102 /** 103 * Returns a random variate distributed accordint to the Student 104 * t distribution with parameters specified by @c param. 105 */ 106 template<class URNG> operator ()(URNG & urng,const param_type & parm) const107 RealType operator()(URNG& urng, const param_type& parm) const 108 { 109 return student_t_distribution(parm)(urng); 110 } 111 112 /** Returns the number of degrees of freedom. */ n() const113 RealType n() const { return _chi_squared.n(); } 114 115 /** Returns the smallest value that the distribution can produce. */ BOOST_PREVENT_MACRO_SUBSTITUTION() const116 RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const 117 { return -std::numeric_limits<RealType>::infinity(); } 118 /** Returns the largest value that the distribution can produce. */ BOOST_PREVENT_MACRO_SUBSTITUTION() const119 RealType max BOOST_PREVENT_MACRO_SUBSTITUTION () const 120 { return std::numeric_limits<RealType>::infinity(); } 121 122 /** Returns the parameters of the distribution. */ param() const123 param_type param() const { return param_type(n()); } 124 /** Sets the parameters of the distribution. */ param(const param_type & parm)125 void param(const param_type& parm) 126 { 127 typedef chi_squared_distribution<RealType> chi_squared_type; 128 typename chi_squared_type::param_type chi_squared_param(parm.n()); 129 _chi_squared.param(chi_squared_param); 130 } 131 132 /** 133 * Effects: Subsequent uses of the distribution do not depend 134 * on values produced by any engine prior to invoking reset. 135 */ reset()136 void reset() 137 { 138 _normal.reset(); 139 _chi_squared.reset(); 140 } 141 142 /** Writes a @c student_t_distribution to a @c std::ostream. */ BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os,student_t_distribution,td)143 BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, student_t_distribution, td) 144 { 145 os << td.param(); 146 return os; 147 } 148 149 /** Reads a @c student_t_distribution from a @c std::istream. */ BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is,student_t_distribution,td)150 BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, student_t_distribution, td) 151 { 152 param_type parm; 153 if(is >> parm) { 154 td.param(parm); 155 } 156 return is; 157 } 158 159 /** 160 * Returns true if the two instances of @c student_t_distribution will 161 * return identical sequences of values given equal generators. 162 */ BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(student_t_distribution,lhs,rhs)163 BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(student_t_distribution, lhs, rhs) 164 { return lhs._normal == rhs._normal && lhs._chi_squared == rhs._chi_squared; } 165 166 /** 167 * Returns true if the two instances of @c student_t_distribution will 168 * return different sequences of values given equal generators. 169 */ 170 BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(student_t_distribution) 171 172 private: 173 normal_distribution<RealType> _normal; 174 chi_squared_distribution<RealType> _chi_squared; 175 }; 176 177 } // namespace random 178 } // namespace boost 179 180 #endif // BOOST_RANDOM_STUDENT_T_DISTRIBUTION_HPP 181