Stan Math Library  2.15.0
reverse mode automatic differentiation
multi_student_t_rng.hpp
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1 #ifndef STAN_MATH_PRIM_MAT_PROB_MULTI_STUDENT_T_RNG_HPP
2 #define STAN_MATH_PRIM_MAT_PROB_MULTI_STUDENT_T_RNG_HPP
3 
4 #include <boost/math/special_functions/gamma.hpp>
5 #include <boost/random/variate_generator.hpp>
20 #include <cstdlib>
21 
22 namespace stan {
23  namespace math {
24 
25  template <class RNG>
26  inline Eigen::VectorXd
28  const Eigen::Matrix<double, Eigen::Dynamic, 1>& mu,
29  const Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic>& s,
30  RNG& rng) {
31  static const char* function("multi_student_t_rng");
32 
33  check_finite(function, "Location parameter", mu);
34  check_symmetric(function, "Scale parameter", s);
35  check_not_nan(function, "Degrees of freedom parameter", nu);
36  check_positive(function, "Degrees of freedom parameter", nu);
37 
38  Eigen::VectorXd z(s.cols());
39  z.setZero();
40 
41  double w = inv_gamma_rng(nu / 2, nu / 2, rng);
42  return mu + std::sqrt(w) * multi_normal_rng(z, s, rng);
43  }
44 
45  }
46 }
47 #endif
void check_finite(const char *function, const char *name, const T_y &y)
Check if y is finite.
fvar< T > sqrt(const fvar< T > &x)
Definition: sqrt.hpp:14
Eigen::VectorXd multi_student_t_rng(double nu, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &mu, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &s, RNG &rng)
void check_not_nan(const char *function, const char *name, const T_y &y)
Check if y is not NaN.
double inv_gamma_rng(double alpha, double beta, RNG &rng)
void check_symmetric(const char *function, const char *name, const Eigen::Matrix< T_y, Eigen::Dynamic, Eigen::Dynamic > &y)
Check if the specified matrix is symmetric.
Eigen::VectorXd multi_normal_rng(const Eigen::VectorXd &mu, const Eigen::MatrixXd &S, RNG &rng)
Return a pseudo-random vector with a multi-variate normal distribution given the specified location p...
void check_positive(const char *function, const char *name, const T_y &y)
Check if y is positive.

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