corr_matrix_constrain() [5/6]

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

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

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

The input vector must be of length \({k \choose 2} = \frac{k(k-1)}{2}\). The values in the input vector represent unconstrained (partial) correlations among the dimensions.

The transform based on partial correlations is as specified in

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

The free vector entries are first constrained to be valid correlation values using corr_constrain(T).

Template Parameters

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

Parameters

x	Vector of unconstrained partial correlations.
k	Dimensionality of returned correlation matrix.

Exceptions

std::invalid_argument

if x is not a valid correlation matrix.

Definition at line 41 of file corr_matrix_constrain.hpp.