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
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) {
19 T_precision>(y, x, alpha,
beta, phi);
25template <
typename T_y,
typename T_x,
typename T_alpha,
typename T_beta,
29 const T_beta &
beta,
const T_precision &phi) {
30 return neg_binomial_2_log_glm_lpmf<false>(y, x, alpha,
beta, phi);
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.
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...