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- #ifndef BOOST_RANDOM_STUDENT_T_DISTRIBUTION_HPP
- #define BOOST_RANDOM_STUDENT_T_DISTRIBUTION_HPP
- #include <boost/config/no_tr1/cmath.hpp>
- #include <iosfwd>
- #include <boost/config.hpp>
- #include <boost/limits.hpp>
- #include <boost/random/detail/operators.hpp>
- #include <boost/random/chi_squared_distribution.hpp>
- #include <boost/random/normal_distribution.hpp>
- namespace boost {
- namespace random {
- template<class RealType = double>
- class student_t_distribution {
- public:
- typedef RealType result_type;
- typedef RealType input_type;
- class param_type {
- public:
- typedef student_t_distribution distribution_type;
-
- explicit param_type(RealType n_arg = RealType(1.0))
- : _n(n_arg)
- {}
-
- RealType n() const { return _n; }
-
- BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
- { os << parm._n; return os; }
-
- BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
- { is >> parm._n; return is; }
-
- BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
- { return lhs._n == rhs._n; }
-
-
- BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
- private:
- RealType _n;
- };
-
- explicit student_t_distribution(RealType n_arg = RealType(1.0))
- : _normal(), _chi_squared(n_arg)
- {}
-
- explicit student_t_distribution(const param_type& parm)
- : _normal(), _chi_squared(parm.n())
- {}
-
- template<class URNG>
- RealType operator()(URNG& urng)
- {
- using std::sqrt;
- return _normal(urng) / sqrt(_chi_squared(urng) / n());
- }
-
- template<class URNG>
- RealType operator()(URNG& urng, const param_type& parm) const
- {
- return student_t_distribution(parm)(urng);
- }
-
- RealType n() const { return _chi_squared.n(); }
-
- RealType min BOOST_PREVENT_MACRO_SUBSTITUTION () const
- { return -std::numeric_limits<RealType>::infinity(); }
-
- RealType max BOOST_PREVENT_MACRO_SUBSTITUTION () const
- { return std::numeric_limits<RealType>::infinity(); }
-
- param_type param() const { return param_type(n()); }
-
- void param(const param_type& parm)
- {
- typedef chi_squared_distribution<RealType> chi_squared_type;
- typename chi_squared_type::param_type chi_squared_param(parm.n());
- _chi_squared.param(chi_squared_param);
- }
-
- void reset()
- {
- _normal.reset();
- _chi_squared.reset();
- }
-
- BOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, student_t_distribution, td)
- {
- os << td.param();
- return os;
- }
-
- BOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, student_t_distribution, td)
- {
- param_type parm;
- if(is >> parm) {
- td.param(parm);
- }
- return is;
- }
-
- BOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(student_t_distribution, lhs, rhs)
- { return lhs._normal == rhs._normal && lhs._chi_squared == rhs._chi_squared; }
-
-
- BOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(student_t_distribution)
- private:
- normal_distribution<RealType> _normal;
- chi_squared_distribution<RealType> _chi_squared;
- };
- }
- }
- #endif
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