Automatic Differentiation
 
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multinomial_logit_log.hpp
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1#ifndef STAN_MATH_PRIM_PROB_MULTINOMIAL_LOGIT_LOG_HPP
2#define STAN_MATH_PRIM_PROB_MULTINOMIAL_LOGIT_LOG_HPP
3
7#include <vector>
8
9namespace stan {
10namespace math {
11
15template <bool propto, typename T_beta,
16 require_eigen_col_vector_t<T_beta>* = nullptr>
18 const T_beta& beta) {
19 return multinomial_logit_lpmf<propto>(ns, beta);
20}
21
25template <typename T_beta, require_eigen_col_vector_t<T_beta>* = nullptr>
27 const T_beta& beta) {
28 return multinomial_logit_lpmf<false>(ns, beta);
29}
30
31} // namespace math
32} // namespace stan
33#endif
return_type_t< T_beta > multinomial_logit_log(const std::vector< int > &ns, const T_beta &beta)
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