Stan Math Library  2.20.0
reverse mode automatic differentiation
poisson_log_glm_log.hpp
Go to the documentation of this file.
1 #ifndef STAN_MATH_PRIM_MAT_PROB_POISSON_LOG_GLM_LOG_HPP
2 #define STAN_MATH_PRIM_MAT_PROB_POISSON_LOG_GLM_LOG_HPP
3 
6 
7 namespace stan {
8 namespace math {
9 
13 template <bool propto, typename T_y, typename T_x, typename T_alpha,
14  typename T_beta>
16  const T_y &y, const T_x &x, const T_alpha &alpha, const T_beta &beta) {
17  return poisson_log_glm_lpmf<propto, T_y, T_x, T_alpha, T_beta>(y, x, alpha,
18  beta);
19 }
20 
24 template <typename T_y, typename T_x, typename T_alpha, typename T_beta>
26  const T_y &y, const T_x &x, const T_alpha &alpha, const T_beta &beta) {
27  return poisson_log_glm_lpmf<false>(y, x, alpha, beta);
28 }
29 } // namespace math
30 } // namespace stan
31 #endif
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
boost::math::tools::promote_args< double, typename scalar_type< T >::type, typename return_type< Types_pack... >::type >::type type
Definition: return_type.hpp:36
return_type< T_x, T_alpha, T_beta >::type poisson_log_glm_log(const T_y &y, const T_x &x, const T_alpha &alpha, const T_beta &beta)

     [ Stan Home Page ] © 2011–2018, Stan Development Team.