cov_matrix_constrain_lkj() [4/5]

template<typename T , require_var_vector_t< T > * = nullptr>

var_value< Eigen::MatrixXd > stan::math::cov_matrix_constrain_lkj	(	const T &	x,
		size_t	k
	)

Return the covariance matrix of the specified dimensionality derived from constraining the specified vector of unconstrained values.

The input vector must be of length $k \choose 2 + k$. The first $k \choose 2$ values in the input represent unconstrained (partial) correlations and the last $k$ are unconstrained standard deviations of the dimensions.

The transform scales the correlation matrix transform defined in corr_matrix_constrain(Matrix, size_t) with the constrained deviations.

Template Parameters

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

Parameters

x	Input vector of unconstrained partial correlations and standard deviations.
k	Dimensionality of returned covariance matrix.

Returns

Covariance matrix derived from the unconstrained partial correlations and deviations.

Definition at line 35 of file cov_matrix_constrain_lkj.hpp.