Automatic Differentiation
 
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◆ multi_normal_cholesky_log() [1/2]

template<bool propto, typename T_y , typename T_loc , typename T_covar >
return_type_t< T_y, T_loc, T_covar > stan::math::multi_normal_cholesky_log ( 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.

Deprecated:
use multi_normal_cholesky_lpdf
Parameters
yA scalar vector
muThe mean vector of the multivariate normal distribution.
LThe Cholesky decomposition of a variance matrix of the multivariate normal distribution
Returns
The log of the multivariate normal density.
Exceptions
std::domain_errorif LL' is not square, not symmetric, or not semi-positive definite.
Template Parameters
T_yType of scalar.
T_locType of location.
T_covarType of scale.

Definition at line 29 of file multi_normal_cholesky_log.hpp.