Automatic Differentiation
 
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inv_wishart_log.hpp
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1#ifndef STAN_MATH_PRIM_PROB_INV_WISHART_LOG_HPP
2#define STAN_MATH_PRIM_PROB_INV_WISHART_LOG_HPP
3
7
8namespace stan {
9namespace math {
10
31template <bool propto, typename T_y, typename T_dof, typename T_scale>
33 const T_dof& nu,
34 const T_scale& S) {
35 return inv_wishart_lpdf<propto>(W, nu, S);
36}
37
41template <typename T_y, typename T_dof, typename T_scale>
43 const T_dof& nu,
44 const T_scale& S) {
45 return inv_wishart_lpdf<>(W, nu, S);
46}
47
48} // namespace math
49} // namespace stan
50#endif
return_type_t< T_y, T_dof, T_scale > inv_wishart_log(const T_y &W, const T_dof &nu, const T_scale &S)
The log of the Inverse-Wishart density for the given W, degrees of freedom, and scale matrix.
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