Automatic Differentiation
 
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◆ wishart_cholesky_lpdf() [1/2]

template<bool propto, typename T_y , typename T_dof , typename T_scale , require_stan_scalar_t< T_dof > * = nullptr, require_all_matrix_t< T_y, T_scale > * = nullptr>
return_type_t< T_y, T_dof, T_scale > stan::math::wishart_cholesky_lpdf ( const T_y &  L_Y,
const T_dof &  nu,
const T_scale &  L_S 
)

Return the natural logarithm of the unnormalized Wishart density of the specified lower-triangular Cholesky factor variate, positive degrees of freedom, and lower-triangular Cholesky factor of the scale matrix.

The scale matrix, L_S, must be a lower Cholesky factor dimension, k, is implicit nu must be greater than k-1

The change of variables from the input positive-definite matrix to the Cholesky factor is given in Theorem 2.1.9 in Muirhead, R. J. (2005). Aspects of Multivariate Statistical Theory. Wiley-Interscience.

Template Parameters
T_yCholesky factor matrix
T_dofscalar degrees of freedom
T_scaleCholesky factor matrix
Parameters
L_Ylower triangular Cholesky factor of the inverse covariance matrix
nuscalar degrees of freedom
L_Slower triangular Cholesky factor of the scale matrix
Returns
natural logarithm of the Wishart density at L_Y given nu and L_S
Exceptions
std::domain_errorif nu is not greater than k-1
std::domain_errorif L_S is not a valid Cholesky factor

Definition at line 42 of file wishart_cholesky_lpdf.hpp.