Automatic Differentiation
 
Loading...
Searching...
No Matches
neg_binomial_2_log_glm_log.hpp
Go to the documentation of this file.
1#ifndef STAN_MATH_PRIM_PROB_NEG_BINOMIAL_2_LOG_GLM_LOG_HPP
2#define STAN_MATH_PRIM_PROB_NEG_BINOMIAL_2_LOG_GLM_LOG_HPP
3
6
7namespace stan {
8namespace math {
9
13template <bool propto, typename T_y, typename T_x, typename T_alpha,
14 typename T_beta, typename T_precision>
16 const T_y &y, const T_x &x, const T_alpha &alpha, const T_beta &beta,
17 const T_precision &phi) {
18 return neg_binomial_2_log_glm_lpmf<propto, T_y, T_x, T_alpha, T_beta,
19 T_precision>(y, x, alpha, beta, phi);
20}
21
25template <typename T_y, typename T_x, typename T_alpha, typename T_beta,
26 typename T_precision>
28neg_binomial_2_log_glm_log(const T_y &y, const T_x &x, const T_alpha &alpha,
29 const T_beta &beta, const T_precision &phi) {
30 return neg_binomial_2_log_glm_lpmf<false>(y, x, alpha, beta, phi);
31}
32} // namespace math
33} // namespace stan
34#endif
return_type_t< T_x, T_alpha, T_beta, T_precision > neg_binomial_2_log_glm_log(const T_y &y, const T_x &x, const T_alpha &alpha, const T_beta &beta, const T_precision &phi)
return_type_t< T_x_cl, T_alpha_cl, T_beta_cl, T_phi_cl > neg_binomial_2_log_glm_lpmf(const T_y_cl &y, const T_x_cl &x, const T_alpha_cl &alpha, const T_beta_cl &beta, const T_phi_cl &phi)
Returns the log PMF of the Generalized Linear Model (GLM) with Negative-Binomial-2 distribution and l...
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