1 #ifndef STAN_MATH_PRIM_MAT_PROB_NEG_BINOMIAL_2_LOG_GLM_LOG_HPP 2 #define STAN_MATH_PRIM_MAT_PROB_NEG_BINOMIAL_2_LOG_GLM_LOG_HPP 13 template <
bool propto,
typename T_y,
typename T_x,
typename T_alpha,
14 typename T_beta,
typename T_precision>
17 const T_beta &
beta,
const T_precision &phi) {
19 T_precision>(y, x, alpha,
beta, phi);
25 template <
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_x, T_alpha, T_beta, T_precision >::type neg_binomial_2_log_glm_lpmf(const T_y &y, const T_x &x, const T_alpha &alpha, const T_beta &beta, const T_precision &phi)
Returns the log PMF of the Generalized Linear Model (GLM) with Negative-Binomial-2 distribution and l...
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.
boost::math::tools::promote_args< double, typename scalar_type< T >::type, typename return_type< Types_pack... >::type >::type type
return_type< T_x, T_alpha, T_beta, T_precision >::type 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)