Automatic Differentiation
 
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pareto_log.hpp
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1#ifndef STAN_MATH_PRIM_PROB_PARETO_LOG_HPP
2#define STAN_MATH_PRIM_PROB_PARETO_LOG_HPP
3
6
7namespace stan {
8namespace math {
9
13template <bool propto, typename T_y, typename T_scale, typename T_shape>
15 const T_scale& y_min,
16 const T_shape& alpha) {
17 return pareto_lpdf<propto, T_y, T_scale, T_shape>(y, y_min, alpha);
18}
19
23template <typename T_y, typename T_scale, typename T_shape>
25 const T_scale& y_min,
26 const T_shape& alpha) {
27 return pareto_lpdf<T_y, T_scale, T_shape>(y, y_min, alpha);
28}
29
30} // namespace math
31} // namespace stan
32#endif
return_type_t< T_y, T_scale, T_shape > pareto_log(const T_y &y, const T_scale &y_min, const T_shape &alpha)
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Definition fvar.hpp:9