Automatic Differentiation
 
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multi_normal_cholesky_log.hpp
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1#ifndef STAN_MATH_PRIM_PROB_MULTI_NORMAL_CHOLESKY_LOG_HPP
2#define STAN_MATH_PRIM_PROB_MULTI_NORMAL_CHOLESKY_LOG_HPP
3
7
8namespace stan {
9namespace math {
28template <bool propto, typename T_y, typename T_loc, typename T_covar>
30 const T_loc& mu,
31 const T_covar& L) {
32 return multi_normal_cholesky_lpdf<propto, T_y, T_loc, T_covar>(y, mu, L);
33}
34
38template <typename T_y, typename T_loc, typename T_covar>
40 const T_y& y, const T_loc& mu, const T_covar& L) {
41 return multi_normal_cholesky_lpdf<T_y, T_loc, T_covar>(y, mu, L);
42}
43
44} // namespace math
45} // namespace stan
46#endif
return_type_t< T_y, T_loc, T_covar > multi_normal_cholesky_log(const T_y &y, const T_loc &mu, const T_covar &L)
The log of the multivariate normal density for the given y, mu, and a Cholesky factor L of the varian...
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Definition fvar.hpp:9