Automatic Differentiation
 
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inv_chi_square_log.hpp
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1#ifndef STAN_MATH_PRIM_PROB_INV_CHI_SQUARE_LOG_HPP
2#define STAN_MATH_PRIM_PROB_INV_CHI_SQUARE_LOG_HPP
3
6
7namespace stan {
8namespace math {
9
32template <bool propto, typename T_y, typename T_dof>
33return_type_t<T_y, T_dof> inv_chi_square_log(const T_y& y, const T_dof& nu) {
34 return inv_chi_square_lpdf<propto, T_y, T_dof>(y, nu);
35}
36
40template <typename T_y, typename T_dof>
42 const T_dof& nu) {
43 return inv_chi_square_lpdf<T_y, T_dof>(y, nu);
44}
45
46} // namespace math
47} // namespace stan
48#endif
return_type_t< T_y, T_dof > inv_chi_square_log(const T_y &y, const T_dof &nu)
The log of an inverse chi-squared density for y with the specified degrees of freedom parameter.
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