studentT_8cpp_source.html

 #include "statsLib.h"


 dvariable dstudent_t( const dvar_vector& residual, const dvar_vector& df)

 {

   RETURN_ARRAYS_INCREMENT();

   double pi =  3.141593;

   dvar_vector t1 = 0.5*(df+1);

   dvar_vector t2 = gammln(t1);

   dvar_vector t3 = 0.5*log(df*pi)+gammln(0.5*df);

   dvar_vector t4 = elem_prod(t1,log(1+elem_div(square(residual),df)));

   dvariable pdf = sum(t3+t4-t2);

   RETURN_ARRAYS_DECREMENT();

   return( pdf );

 }

elem_prod
d3_array elem_prod(const d3_array &a, const d3_array &b)
Returns d3_array results with computed elements product of a(i, j, k) * b(i, j, k).
Definition: d3arr2a.cpp:92

gammln
double gammln(double xx)
Log gamma function.
Definition: combc.cpp:52

RETURN_ARRAYS_DECREMENT
void RETURN_ARRAYS_DECREMENT(void)
Decrements gradient_structure::RETURN_ARRAYS_PTR.
Definition: gradstrc.cpp:507

sum
double sum(const d3_array &darray)
Author: David Fournier Copyright (c) 2008-2012 Regents of the University of California.
Definition: d3arr.cpp:21

elem_div
d3_array elem_div(const d3_array &a, const d3_array &b)
Returns d3_array results with computed elements division of a(i, j, k) / b(i, j, k).
Definition: d3arr2a.cpp:112

dvar_vector
ADMB variable vector.
Definition: fvar.hpp:2172

statsLib.h
Library of statistic functions.

dstudent_t
dvariable dstudent_t(const dvar_vector &residual, const dvar_vector &df)
Definition: studentT.cpp:38

RETURN_ARRAYS_INCREMENT
void RETURN_ARRAYS_INCREMENT(void)
Increments gradient_structure::RETURN_ARRAYS_PTR.
Definition: gradstrc.cpp:474

square
double square(const double value)
Return square of value; constant object.
Definition: d3arr4.cpp:16

dvariable
Fundamental data type for reverse mode automatic differentiation.
Definition: fvar.hpp:1518

log
d3_array log(const d3_array &arr3)
Author: David Fournier Copyright (c) 2008-2012 Regents of the University of California.
Definition: d3arr2a.cpp:13