Stan Math Library  2.14.0
reverse mode automatic differentiation
log_rising_factorial.hpp
Go to the documentation of this file.
1 #ifndef STAN_MATH_FWD_SCAL_FUN_LOG_RISING_FACTORIAL_HPP
2 #define STAN_MATH_FWD_SCAL_FUN_LOG_RISING_FACTORIAL_HPP
3 
4 #include <stan/math/fwd/core.hpp>
5 
8 
9 namespace stan {
10  namespace math {
11 
12  template<typename T>
13  inline fvar<T> log_rising_factorial(const fvar<T>& x, const fvar<T>& n) {
15  digamma(x.val_ + n.val_) * (x.d_ + n.d_)
16  - digamma(x.val_) * x.d_);
17  }
18 
19  template<typename T>
20  inline fvar<T> log_rising_factorial(const fvar<T>& x, double n) {
21  return fvar<T>(log_rising_factorial(x.val_, n),
22  (digamma(x.val_ + n) - digamma(x.val_)) * x.d_);
23  }
24 
25  template<typename T>
26  inline fvar<T> log_rising_factorial(double x, const fvar<T>& n) {
27  return fvar<T>(log_rising_factorial(x, n.val_),
28  digamma(x + n.val_) * n.d_);
29  }
30 
31  }
32 }
33 #endif
fvar< T > log_rising_factorial(const fvar< T > &x, const fvar< T > &n)
fvar< T > digamma(const fvar< T > &x)
Return the derivative of the log gamma function at the specified argument.
Definition: digamma.hpp:22

     [ Stan Home Page ] © 2011–2016, Stan Development Team.