Automatic Differentiation
 
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rising_factorial.hpp
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1#ifndef STAN_MATH_FWD_FUN_RISING_FACTORIAL_HPP
2#define STAN_MATH_FWD_FUN_RISING_FACTORIAL_HPP
3
8
9namespace stan {
10namespace math {
11
25template <typename T>
26inline fvar<T> rising_factorial(const fvar<T>& x, int n) {
27 T rising_fact(rising_factorial(x.val_, n));
28 return fvar<T>(rising_fact,
29 rising_fact * x.d_ * (digamma(x.val_ + n) - digamma(x.val_)));
30}
31
32} // namespace math
33} // namespace stan
34#endif
fvar< T > rising_factorial(const fvar< T > &x, int n)
Return autodiff variable with the gradient and result of the rising factorial function applied to the...
fvar< T > digamma(const fvar< T > &x)
Return the derivative of the log gamma function at the specified argument.
Definition digamma.hpp:23
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Scalar val_
The value of this variable.
Definition fvar.hpp:49
Scalar d_
The tangent (derivative) of this variable.
Definition fvar.hpp:61
This template class represents scalars used in forward-mode automatic differentiation,...
Definition fvar.hpp:40