Automatic Differentiation
 
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log1m.hpp
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1#ifndef STAN_MATH_REV_FUN_LOG1M_HPP
2#define STAN_MATH_REV_FUN_LOG1M_HPP
3
7
8namespace stan {
9namespace math {
10
22template <typename T, require_stan_scalar_or_eigen_t<T>* = nullptr>
23inline auto log1m(const var_value<T>& a) {
24 return make_callback_var(log1m(a.val()), [a](auto& vi) mutable {
25 as_array_or_scalar(a.adj())
26 += as_array_or_scalar(vi.adj()) / (as_array_or_scalar(a.val()) - 1.0);
27 });
28}
29
30} // namespace math
31} // namespace stan
32#endif
var_value< plain_type_t< T > > make_callback_var(T &&value, F &&functor)
Creates a new var initialized with a callback_vari with a given value and reverse-pass callback funct...
fvar< T > log1m(const fvar< T > &x)
Definition log1m.hpp:12
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...