Automatic Differentiation
 
Loading...
Searching...
No Matches
asinh.hpp
Go to the documentation of this file.
1#ifndef STAN_MATH_FWD_FUN_ASINH_HPP
2#define STAN_MATH_FWD_FUN_ASINH_HPP
3
8#include <cmath>
9#include <complex>
10
11namespace stan {
12namespace math {
13
14template <typename T>
15inline fvar<T> asinh(const fvar<T>& x) {
16 using std::sqrt;
17 return fvar<T>(asinh(x.val_), x.d_ / sqrt(square(x.val_) + 1));
18}
19
27template <typename T>
28inline std::complex<fvar<T>> asinh(const std::complex<fvar<T>>& z) {
30}
31
32} // namespace math
33} // namespace stan
34#endif
std::complex< V > complex_asinh(const std::complex< V > &z)
Return the hyperbolic arc sine of the complex argument.
Definition asinh.hpp:62
fvar< T > asinh(const fvar< T > &x)
Definition asinh.hpp:15
fvar< T > sqrt(const fvar< T > &x)
Definition sqrt.hpp:17
fvar< T > square(const fvar< T > &x)
Definition square.hpp:12
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