Automatic Differentiation
 
Loading...
Searching...
No Matches
wiener_log.hpp
Go to the documentation of this file.
1#ifndef STAN_MATH_PRIM_PROB_WIENER_LOG_HPP
2#define STAN_MATH_PRIM_PROB_WIENER_LOG_HPP
3
6
7namespace stan {
8namespace math {
9
30template <bool propto, typename T_y, typename T_alpha, typename T_tau,
31 typename T_beta, typename T_delta>
33 const T_y& y, const T_alpha& alpha, const T_tau& tau, const T_beta& beta,
34 const T_delta& delta) {
35 return wiener_lpdf<propto, T_y, T_alpha, T_tau, T_beta, T_delta>(
36 y, alpha, tau, beta, delta);
37}
38
42template <typename T_y, typename T_alpha, typename T_tau, typename T_beta,
43 typename T_delta>
45 const T_y& y, const T_alpha& alpha, const T_tau& tau, const T_beta& beta,
46 const T_delta& delta) {
47 return wiener_lpdf<T_y, T_alpha, T_tau, T_beta, T_delta>(y, alpha, tau, beta,
48 delta);
49}
50
51} // namespace math
52} // namespace stan
53#endif
return_type_t< T_y, T_alpha, T_tau, T_beta, T_delta > wiener_log(const T_y &y, const T_alpha &alpha, const T_tau &tau, const T_beta &beta, const T_delta &delta)
The log of the first passage time density function for a (Wiener) drift diffusion model for the given...
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
fvar< T > beta(const fvar< T > &x1, const fvar< T > &x2)
Return fvar with the beta function applied to the specified arguments and its gradient.
Definition beta.hpp:51
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Definition fvar.hpp:9