multi_normal_cholesky_lpdf() [2/3]

template<bool propto, typename T_y , typename T_loc , typename T_covar , require_any_not_vector_vt< is_stan_scalar, T_y, 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_loc, T_covar > stan::math::multi_normal_cholesky_lpdf	(	const T_y &	y,
		const T_loc &	mu,
		const T_covar &	L
	)

The log of the multivariate normal density for the given y, mu, and a Cholesky factor L of the variance matrix.

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

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

Analytic expressions taken from http://qwone.com/~jason/writing/multivariateNormal.pdf written by Jason D. M. Rennie.

Parameters

y	A scalar vector
mu	The mean vector of the multivariate normal distribution.
L	The Cholesky decomposition of a variance matrix of the multivariate normal distribution

Returns

The log of the multivariate normal density.

Exceptions

std::domain_error

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

Template Parameters

T_y	Type of scalar.
T_loc	Type of location.
T_covar	Type of scale.

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

Analytic expressions taken from http://qwone.com/~jason/writing/multivariateNormal.pdf written by Jason D. M. Rennie.

Parameters

y	A scalar vector
mu	The mean vector of the multivariate normal distribution.
L	The Cholesky decomposition of a variance matrix of the multivariate normal distribution

Returns

The log of the multivariate normal density.

Exceptions

std::domain_error

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

Template Parameters

T_y	Type of scalar.
T_loc	Type of location.
T_covar	Type of scale.

Definition at line 48 of file multi_normal_cholesky_lpdf.hpp.