Automatic Differentiation
 
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log1m_exp.hpp
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1#ifndef STAN_MATH_FWD_FUN_LOG1M_EXP_HPP
2#define STAN_MATH_FWD_FUN_LOG1M_EXP_HPP
3
9
10namespace stan {
11namespace math {
12
21template <typename T>
22inline fvar<T> log1m_exp(const fvar<T>& x) {
23 if (x.val_ >= 0) {
24 return fvar<T>(NOT_A_NUMBER);
25 }
26 return fvar<T>(log1m_exp(x.val_), x.d_ / -expm1(-x.val_));
27}
28
29} // namespace math
30} // namespace stan
31#endif
static constexpr double NOT_A_NUMBER
(Quiet) not-a-number value.
Definition constants.hpp:56
fvar< T > expm1(const fvar< T > &x)
Definition expm1.hpp:14
fvar< T > log1m_exp(const fvar< T > &x)
Return the natural logarithm of one minus the exponentiation of the specified argument.
Definition log1m_exp.hpp:22
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