source: trunk/yat/regression/OneDimensional.cc @ 727

Last change on this file since 727 was 727, checked in by Peter, 15 years ago

fixes #177

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id
File size: 1.7 KB
Line 
1// $Id: OneDimensional.cc 727 2007-01-04 15:06:14Z peter $
2
3/*
4  Copyright (C) The authors contributing to this file.
5
6  This file is part of the yat library, http://lev.thep.lu.se/trac/yat
7
8  The yat library is free software; you can redistribute it and/or
9  modify it under the terms of the GNU General Public License as
10  published by the Free Software Foundation; either version 2 of the
11  License, or (at your option) any later version.
12
13  The yat library is distributed in the hope that it will be useful,
14  but WITHOUT ANY WARRANTY; without even the implied warranty of
15  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
16  General Public License for more details.
17
18  You should have received a copy of the GNU General Public License
19  along with this program; if not, write to the Free Software
20  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
21  02111-1307, USA.
22*/
23
24#include "OneDimensional.h"
25
26namespace theplu {
27namespace yat {
28namespace regression {
29
30  OneDimensional::OneDimensional(void)
31  {
32  }
33
34  OneDimensional::~OneDimensional(void)
35  {
36  }
37
38
39  double OneDimensional::prediction_error2(const double x) const 
40  { 
41    return chisq()+standard_error2(x); 
42  }
43
44
45  std::ostream& OneDimensional::print(std::ostream& os, const double min, 
46                                      double max, const u_int n) const
47  {
48    double dx;
49    if (n>1)
50      dx=(max-min)/(n-1);
51    else{
52      dx=1.0;
53      max=min;
54    }
55
56    for ( double x=min; x<=max; x+=dx) {
57      double y = predict(x);
58      double y_err = sqrt(prediction_error2(x));
59      os << x << "\t" << y << "\t" << y_err << "\n";
60    }
61    return os;
62  }
63
64
65  double OneDimensional::r_squared(void) const
66  {
67    return chisq()/variance();
68  }
69
70  double OneDimensional::variance(void) const
71  {
72    return ap_.y_averager().variance();
73  }
74
75}}} // of namespaces regression, yat, and theplu
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