13 static double cc=0.39894228040143267794;
15 typedef double (*
pinit_f)(
double y,
double a);
35 double dfx=
cc*(0.95*
exp(-0.5*x2)+0.05/a*
exp(-0.5*x2/(a*a)) );
69 double x=(*p_get_initial_x)(y,3.0);
76 double cy=(*pfun)(
x,3.0);
77 double der=(*pdfun)(
x,3.0);
81 if (
fabs(h)<1.e-12)
break;
Base class for dvariable.
#define ADUNCONST(type, obj)
Creates a shallow copy of obj that is not CONST.
double inv_cumd_norm(const double &x)
Description not yet available.
df1_two_variable fabs(const df1_two_variable &x)
static double cumd_normal_mixture_initx(double y, double a)
Description not yet available.
static double cumd_normal_mixture(double x, double a)
Description not yet available.
void set_gradient_stack(void(*func)(void), double *dep_addr, double *ind_addr1=NULL, double mult1=0, double *ind_addr2=NULL, double mult2=0)
Description not yet available.
static double df_cumd_normal_mixture(double x, double a)
Description not yet available.
Author: David Fournier Copyright (c) 2008-2012 Regents of the University of California.
d3_array exp(const d3_array &arr3)
Returns d3_array results with computed exp from elements in arr3.
void default_evaluation(void)
Description not yet available.
double(* pinit_f)(double y, double a)
double nr_generic(double y, double a, pinit_f p_get_initial_x, pinit_f pfun, pinit_f pdfun)
Description not yet available.
dvector value(const df1_one_vector &v)
static _THREAD grad_stack * GRAD_STACK1
double cumd_norm(const double &x)
Culative normal distribution; constant objects.
double inv_cumd_normal_mixture(double yy, double a)
Description not yet available.
Fundamental data type for reverse mode automatic differentiation.