Automatic Differentiation
 
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beta_cdf_log.hpp
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1#ifndef STAN_MATH_PRIM_PROB_BETA_CDF_LOG_HPP
2#define STAN_MATH_PRIM_PROB_BETA_CDF_LOG_HPP
3
6
7namespace stan {
8namespace math {
9
13template <typename T_y, typename T_scale_succ, typename T_scale_fail>
15 const T_y& y, const T_scale_succ& alpha, const T_scale_fail& beta) {
16 return beta_lcdf<T_y, T_scale_succ, T_scale_fail>(y, alpha, beta);
17}
18
19} // namespace math
20} // namespace stan
21#endif
return_type_t< T_y, T_scale_succ, T_scale_fail > beta_cdf_log(const T_y &y, const T_scale_succ &alpha, const T_scale_fail &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 ...