cov_matrix_constrain_lkj() [1/5]

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

Eigen::Matrix< value_type_t< T >, Eigen::Dynamic, Eigen::Dynamic > stan::math::cov_matrix_constrain_lkj ( const T &  x, size_t  k  )

inline

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 the vector (must be derived from Eigen::MatrixBase and have one compile-time dimension equal to 1)

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.