◆ multi_student_t_cholesky_lpdf() [1/2]

template<bool propto, typename T_y , typename T_dof , typename T_loc , typename T_covar , require_any_not_vector_vt< is_stan_scalar, T_y, T_dof, T_loc > * = nullptr, require_all_not_nonscalar_prim_or_rev_kernel_expression_t< T_y, T_loc, T_covar > * = nullptr>

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
	)

inline

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.

Parameters

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.

Exceptions

std::domain_error if LL' is not square, not symmetric, or not semi-positive definite.

Template Parameters

Sigma = LL', a square, semi-positive definite matrix.

This version of the function is vectorized on y and mu.

Parameters

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.

Exceptions

std::domain_error if LL' is not square, not symmetric, or not semi-positive definite.

Template Parameters