Automatic Differentiation
 
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lmgamma.hpp
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1#ifndef STAN_MATH_PRIM_FUN_LMGAMMA_HPP
2#define STAN_MATH_PRIM_FUN_LMGAMMA_HPP
3
9
10namespace stan {
11namespace math {
12
54template <typename T, require_arithmetic_t<T>* = nullptr>
55inline return_type_t<T> lmgamma(int k, T x) {
56 return_type_t<T> result = k * (k - 1) * LOG_PI_OVER_FOUR;
57
58 return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2));
59}
60
72template <typename T1, typename T2, require_any_container_t<T1, T2>* = nullptr>
73inline auto lmgamma(const T1& a, const T2& b) {
75 a, b, [&](const auto& c, const auto& d) { return lmgamma(c, d); });
76}
77
78} // namespace math
79} // namespace stan
80#endif
typename return_type< Ts... >::type return_type_t
Convenience type for the return type of the specified template parameters.
static constexpr double LOG_PI_OVER_FOUR
The value of one quarter the natural logarithm of , .
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition sum.hpp:22
fvar< return_type_t< T, int > > lmgamma(int x1, const fvar< T > &x2)
Definition lmgamma.hpp:14
fvar< T > lgamma(const fvar< T > &x)
Return the natural logarithm of the gamma function applied to the specified argument.
Definition lgamma.hpp:21
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 ...
Definition fvar.hpp:9