Automatic Differentiation
 
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log_inv_logit.hpp
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1#ifndef STAN_MATH_FWD_FUN_LOG_INV_LOGIT_HPP
2#define STAN_MATH_FWD_FUN_LOG_INV_LOGIT_HPP
3
8#include <cmath>
9
10namespace stan {
11namespace math {
12
13template <typename T>
14inline fvar<T> log_inv_logit(const fvar<T>& x) {
15 return fvar<T>(log_inv_logit(x.val_), x.d_ * inv_logit(-x.val_));
16}
17} // namespace math
18} // namespace stan
19#endif
fvar< T > log_inv_logit(const fvar< T > &x)
fvar< T > inv_logit(const fvar< T > &x)
Returns the inverse logit function applied to the argument.
Definition inv_logit.hpp:20
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