Automatic Differentiation
 
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owens_t.hpp
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1#ifndef STAN_MATH_PRIM_FUN_OWENS_T_HPP
2#define STAN_MATH_PRIM_FUN_OWENS_T_HPP
3
6#include <boost/math/special_functions/owens_t.hpp>
7
8namespace stan {
9namespace math {
10
58inline double owens_t(double h, double a) { return boost::math::owens_t(h, a); }
59
70template <typename T1, typename T2, require_any_container_t<T1, T2>* = nullptr,
71 require_all_not_var_and_matrix_types<T1, T2>* = nullptr>
72inline auto owens_t(const T1& a, const T2& b) {
74 a, b, [](const auto& c, const auto& d) { return owens_t(c, d); });
75}
76
77} // namespace math
78} // namespace stan
79
80#endif
fvar< T > owens_t(const fvar< T > &x1, const fvar< T > &x2)
Return Owen's T function applied to the specified arguments.
Definition owens_t.hpp:25
auto apply_scalar_binary(const T1 &x, const T2 &y, const F &f)
Base template function for vectorization of binary scalar functions defined by applying a functor to ...
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...