corr_matrix_constrain() [5/7]

template<bool Jacobian, typename T , typename Lp , require_convertible_t< return_type_t< T >, Lp > * = nullptr>

auto stan::math::corr_matrix_constrain ( const T &  x, Eigen::Index  k, Lp &  lp  )

inline

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. If the Jacobian parameter is true, the log density accumulator is incremented with the log absolute Jacobian determinant of the transform. All of the transforms are specified with their Jacobians in the Stan Reference Manual chapter Constraint Transforms.

Template Parameters

Jacobian	if true, increment log density accumulator with log absolute Jacobian determinant of constraining transform
T	A type inheriting from Eigen::DenseBase or a var_value with inner type inheriting from Eigen::DenseBase with compile time dynamic rows and 1 column or standard vector thereof
Lp	A scalar type for the lp argument. The scalar type of T should be convertable to this.

Parameters

	x	Vector of unconstrained partial correlations
	k	Dimensionality of returned correlation matrix
[in,out]	lp	log density accumulator

Definition at line 145 of file corr_matrix_constrain.hpp.