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model37.cpp
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1 /*
2  * $Id$
3  *
4  * Author: David Fournier
5  * Copyright (c) 2008-2012 Regents of the University of California
6  */
7 #include <admodel.h>
8 
10  {
11  cout << "You must define the function user_randeff in your TPL"
12  " file to use the random effects optimization" << endl;
13  ad_exit(1);
14 
15  dvariable u;
16  return u;
17  }
19  {
20  cout << "You must define the function user_dfrandeff in your TPL"
21  " file to use the random effects optimization" << endl;
22  ad_exit(1);
23  dvar_vector u;
24  return u;
25  }
27  {
28  cout << "You must define the function user_d2frandeff in your TPL"
29  " file to use the random effects optimization" << endl;
30  ad_exit(1);
31  dvar_matrix u;
32  return u;
33  }
#define x
exitptr ad_exit
Definition: gradstrc.cpp:53
ADMB variable vector.
Definition: fvar.hpp:2172
virtual dvar_vector user_dfrandeff(const dvar_vector &x)
Definition: model37.cpp:18
prnstream & endl(prnstream &)
Description not yet available.
virtual dvar_matrix user_d2frandeff(const dvar_vector &x)
Definition: model37.cpp:26
Class definition of matrix with derivitive information .
Definition: fvar.hpp:2480
virtual dvariable user_randeff(const dvar_vector &x)
Definition: model37.cpp:9
Fundamental data type for reverse mode automatic differentiation.
Definition: fvar.hpp:1518