read_corr_L() [4/4]

template<typename T1 , typename T2 , require_var_vector_t< T1 > * = nullptr, require_stan_scalar_t< T2 > * = nullptr>

auto stan::math::read_corr_L	(	const T1 &	CPCs,
		size_t	K,
		T2 &	log_prob
	)

Return the Cholesky factor of the correlation matrix of the specified dimensionality corresponding to the specified canonical partial correlations, incrementing the specified scalar reference with the log absolute determinant of the Jacobian of the transformation.

The implementation is Ben Goodrich's Cholesky factor-based approach to the C-vine method of:

• Daniel Lewandowski, Dorota Kurowicka, and Harry Joe, Generating random correlation matrices based on vines and extended onion method Journal of Multivariate Analysis 100 (2009) 1989–2001

Template Parameters

T	type of input vector (must be a var_value<S> where S inherits from EigenBase)

Parameters

CPCs	The (K choose 2) canonical partial correlations in (-1, 1).
K	Dimensionality of correlation matrix.
log_prob	Reference to variable to increment with the log Jacobian determinant.

Returns

Cholesky factor of correlation matrix for specified partial correlations.

Definition at line 135 of file read_corr_L.hpp.