1 #ifndef STAN_MATH_PRIM_MAT_PROB_BERNOULLI_LOGIT_GLM_LOG_HPP 2 #define STAN_MATH_PRIM_MAT_PROB_BERNOULLI_LOGIT_GLM_LOG_HPP 13 template <
bool propto,
typename T_y,
typename T_x,
typename T_alpha,
16 const T_y &y,
const T_x &x,
const T_alpha &alpha,
const T_beta &
beta) {
17 return bernoulli_logit_glm_lpmf<propto, T_y, T_x, T_alpha, T_beta>(
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 bernoulli_logit_glm_lpmf<false>(y, x, alpha,
beta);
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 >::type bernoulli_logit_glm_log(const T_y &y, const T_x &x, const T_alpha &alpha, const T_beta &beta)