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Automatic Differentiation
 
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std_normal_log_qf.hpp
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1#ifndef STAN_MATH_FWD_PROB_STD_NORMAL_LOG_QF_HPP
2#define STAN_MATH_FWD_PROB_STD_NORMAL_LOG_QF_HPP
3
11#include <cmath>
12
13namespace stan {
14namespace math {
15
16template <typename T>
18 const T xv = std_normal_log_qf(p.val_);
19 return fvar<T>(xv, p.d_ * exp(p.val_ - std_normal_lpdf(xv)));
20}
21} // namespace math
22} // namespace stan
23#endif
return_type_t< T_y_cl > std_normal_lpdf(const T_y_cl &y)
The log of the normal density for the specified scalar(s) given a location of 0 and a scale of 1.
fvar< T > std_normal_log_qf(const fvar< T > &p)
fvar< T > exp(const fvar< T > &x)
Definition exp.hpp:15
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