cholesky_factor_constrain() [5/5]

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

var_value< Eigen::MatrixXd > stan::math::cholesky_factor_constrain	(	const T &	x,
		int	M,
		int	N,
		scalar_type_t< T > &	lp
	)

Return the Cholesky factor of the specified size read from the specified vector and increment the specified log probability reference with the log Jacobian adjustment of the transform.

A total of (N choose 2) + N + N * (M - N) free parameters are required to read an M by N Cholesky factor.

Template Parameters

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

Parameters

	x	Vector of unconstrained values
	M	number of rows
	N	number of columns
[out]	lp	Log density that is incremented with the log Jacobian

Returns

Cholesky factor

Definition at line 89 of file cholesky_factor_constrain.hpp.