Stan Math Library  2.20.0
reverse mode automatic differentiation
gamma_log.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_PROB_GAMMA_LOG_HPP
2 #define STAN_MATH_PRIM_SCAL_PROB_GAMMA_LOG_HPP
3 
6 
7 namespace stan {
8 namespace math {
9 
35 template <bool propto, typename T_y, typename T_shape, typename T_inv_scale>
37  const T_y& y, const T_shape& alpha, const T_inv_scale& beta) {
38  return gamma_lpdf<propto, T_y, T_shape, T_inv_scale>(y, alpha, beta);
39 }
40 
44 template <typename T_y, typename T_shape, typename T_inv_scale>
46  const T_y& y, const T_shape& alpha, const T_inv_scale& beta) {
47  return gamma_lpdf<T_y, T_shape, T_inv_scale>(y, alpha, beta);
48 }
49 
50 } // namespace math
51 } // namespace stan
52 #endif
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
boost::math::tools::promote_args< double, typename scalar_type< T >::type, typename return_type< Types_pack... >::type >::type type
Definition: return_type.hpp:36
return_type< T_y, T_shape, T_inv_scale >::type gamma_log(const T_y &y, const T_shape &alpha, const T_inv_scale &beta)
The log of a gamma density for y with the specified shape and inverse scale parameters.
Definition: gamma_log.hpp:36

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