1 #ifndef STAN_MATH_REV_SCAL_FUN_GAMMA_P_HPP 2 #define STAN_MATH_REV_SCAL_FUN_GAMMA_P_HPP 26 avi_->
adj_ += std::numeric_limits<double>::quiet_NaN();
27 bvi_->
adj_ += std::numeric_limits<double>::quiet_NaN();
31 avi_->
adj_ += std::numeric_limits<double>::quiet_NaN();
32 bvi_->
adj_ += std::numeric_limits<double>::quiet_NaN();
55 avi_->
adj_ += std::numeric_limits<double>::quiet_NaN();
59 avi_->
adj_ += std::numeric_limits<double>::quiet_NaN();
78 bvi_->
adj_ += std::numeric_limits<double>::quiet_NaN();
82 bvi_->
adj_ += std::numeric_limits<double>::quiet_NaN();
fvar< T > lgamma(const fvar< T > &x)
Return the natural logarithm of the gamma function applied to the specified argument.
fvar< T > fabs(const fvar< T > &x)
gamma_p_vd_vari(vari *avi, double b)
fvar< T > log(const fvar< T > &x)
The variable implementation base class.
gamma_p_vv_vari(vari *avi, vari *bvi)
Independent (input) and dependent (output) variables for gradients.
const double val_
The value of this variable.
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
fvar< T > exp(const fvar< T > &x)
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
vari * vi_
Pointer to the implementation of this variable.
gamma_p_dv_vari(double a, vari *bvi)
int is_inf(const fvar< T > &x)
Returns 1 if the input's value is infinite and 0 otherwise.
fvar< T > gamma_p(const fvar< T > &x1, const fvar< T > &x2)
double adj_
The adjoint of this variable, which is the partial derivative of this variable with respect to the ro...
void chain()
Apply the chain rule to this variable based on the variables on which it depends. ...
return_type< T1, T2 >::type grad_reg_lower_inc_gamma(const T1 &a, const T2 &z, double precision=1e-10, int max_steps=1e5)
Computes the gradient of the lower regularized incomplete gamma function.