Automatic Differentiation
 
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student_t_log.hpp
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1#ifndef STAN_MATH_PRIM_PROB_STUDENT_T_LOG_HPP
2#define STAN_MATH_PRIM_PROB_STUDENT_T_LOG_HPP
3
6
7namespace stan {
8namespace math {
9
40template <bool propto, typename T_y, typename T_dof, typename T_loc,
41 typename T_scale>
43 const T_dof& nu,
44 const T_loc& mu,
45 const T_scale& sigma) {
46 return student_t_lpdf<propto, T_y, T_dof, T_loc, T_scale>(y, nu, mu, sigma);
47}
48
52template <typename T_y, typename T_dof, typename T_loc, typename T_scale>
54 const T_y& y, const T_dof& nu, const T_loc& mu, const T_scale& sigma) {
55 return student_t_lpdf<T_y, T_dof, T_loc, T_scale>(y, nu, mu, sigma);
56}
57
58} // namespace math
59} // namespace stan
60#endif
return_type_t< T_y, T_dof, T_loc, T_scale > student_t_log(const T_y &y, const T_dof &nu, const T_loc &mu, const T_scale &sigma)
The log of the Student-t density for the given y, nu, mean, and scale parameter.
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