Automatic Differentiation
 
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◆ multi_student_t_cholesky_rng()

template<typename T_loc , class RNG >
StdVectorBuilder< true, Eigen::VectorXd, T_loc >::type stan::math::multi_student_t_cholesky_rng ( double  nu,
const T_loc &  mu,
const Eigen::MatrixXd &  L,
RNG &  rng 
)
inline

Return a multivariate student-t random variate with the given degrees of freedom location and Cholesky factor the scale matrix using the specified random number generator.

mu can be either an Eigen::VectorXd, an Eigen::RowVectorXd, or a std::vector of either of those types.

Template Parameters
t_locType of location parameter
rngtype of pseudo-random number generator
Parameters
nua scalar indicating the degrees of freedom parameter
muAn Eigen::VectorXd, Eigen::RowVectorXd, or std::vector of location values for the multivariate student t
Lcholesky factor of the scale matrix
rngrandom number generator
Returns
eigen vector of multivariate student t random variates with the given nu, mu, L
Exceptions
std::domain_errorif L is not a Cholesky factor, any value in mu is not finite, nu is not positive, or nu is NaN
std::invalid_argumentif the length of (each) mu is not equal to the number of rows and columns in L

Definition at line 42 of file multi_student_t_cholesky_rng.hpp.