Stan Math Library
5.0.0
Automatic Differentiation
|
return_type_t< T_y, T_dof, T_loc, T_covar > stan::math::multi_student_t_cholesky_lpdf | ( | const T_y & | y, |
const T_dof & | nu, | ||
const T_loc & | mu, | ||
const T_covar & | L | ||
) |
The log of the multivariate student t density for the given y, mu, nu, and a Cholesky factor L of the scale matrix.
Sigma = LL', a square, semi-positive definite matrix.
This version of the function is vectorized on y and mu.
y | scalar vector of random variates |
nu | scalar degrees of freedom |
mu | location vector |
L | cholesky decomposition of the scale matrix of the multivariate student t distribution. |
std::domain_error | if LL' is not square, not symmetric, or not semi-positive definite. |
T_y | Type of scalar. |
T_dof | Type of scalar. |
T_loc | Type of location. |
T_covar | Type of scale. |
Sigma = LL', a square, semi-positive definite matrix.
This version of the function is vectorized on y and mu.
y | A scalar vector. |
nu | A scalar degrees of freedom. |
mu | A location vector. |
L | The Cholesky decomposition of the scale matrix of the multivariate student t distribution. |
std::domain_error | if LL' is not square, not symmetric, or not semi-positive definite. |
T_y | Type of scalar. |
T_dof | Type of scalar. |
T_loc | Type of location. |
T_covar | Type of scale. |
Definition at line 57 of file multi_student_t_cholesky_lpdf.hpp.