Automatic Differentiation
 
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lkj_corr_rng.hpp
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1#ifndef STAN_MATH_PRIM_PROB_LKJ_CORR_RNG_HPP
2#define STAN_MATH_PRIM_PROB_LKJ_CORR_RNG_HPP
3
8
9namespace stan {
10namespace math {
11
25template <class RNG>
26inline Eigen::MatrixXd lkj_corr_rng(size_t K, double eta, RNG& rng) {
27 static constexpr const char* function = "lkj_corr_rng";
28 check_positive(function, "Shape parameter", eta);
30}
31
32} // namespace math
33} // namespace stan
34#endif
Eigen::MatrixXd lkj_corr_rng(size_t K, double eta, RNG &rng)
Return a random correlation matrix (symmetric, positive definite, unit diagonal) of the specified dim...
Eigen::Matrix< value_type_t< EigMat >, EigMat::RowsAtCompileTime, EigMat::RowsAtCompileTime > multiply_lower_tri_self_transpose(const EigMat &m)
Eigen::MatrixXd lkj_corr_cholesky_rng(size_t K, double eta, RNG &rng)
void check_positive(const char *function, const char *name, const T_y &y)
Check if y is positive.
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Definition fvar.hpp:9