source: trunk/yat/regression/OneDimensional.cc

Last change on this file was 2919, checked in by Peter, 9 years ago

update copyright years

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id
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1// $Id: OneDimensional.cc 2919 2012-12-19 06:54:23Z peter $
2
3/*
4  Copyright (C) 2005 Peter Johansson
5  Copyright (C) 2006, 2007, 2008 Jari Häkkinen, Peter Johansson
6  Copyright (C) 2011, 2012 Peter Johansson
7
8  This file is part of the yat library, http://dev.thep.lu.se/yat
9
10  The yat library is free software; you can redistribute it and/or
11  modify it under the terms of the GNU General Public License as
12  published by the Free Software Foundation; either version 3 of the
13  License, or (at your option) any later version.
14
15  The yat library is distributed in the hope that it will be useful,
16  but WITHOUT ANY WARRANTY; without even the implied warranty of
17  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
18  General Public License for more details.
19
20  You should have received a copy of the GNU General Public License
21  along with yat. If not, see <http://www.gnu.org/licenses/>.
22*/
23
24#include <config.h>
25
26#include "OneDimensional.h"
27
28#include <ostream>
29
30namespace theplu {
31namespace yat {
32namespace regression {
33
34  OneDimensional::OneDimensional(void)
35    : chisq_(0)
36  {
37  }
38
39  OneDimensional::~OneDimensional(void)
40  {
41  }
42
43
44  double OneDimensional::chisq(void) const
45  {
46    return chisq_;
47  }
48
49
50  double OneDimensional::prediction_error2(const double x) const 
51  { 
52    return s2()+standard_error2(x); 
53  }
54
55
56  std::ostream& OneDimensional::print(std::ostream& os, const double min, 
57                                      double max, const unsigned int n) const
58  {
59    double dx;
60    if (n>1)
61      dx=(max-min)/(n-1);
62    else{
63      dx=1.0;
64      max=min;
65    }
66
67    for ( double x=min; x<=max; x+=dx) {
68      double y = predict(x);
69      double y_err = sqrt(prediction_error2(x));
70      os << x << "\t" << y << "\t" << y_err << "\n";
71    }
72    return os;
73  }
74
75
76  double OneDimensional::r2(void) const
77  {
78    return 1 - chisq()/ap_.y_averager().sum_xx_centered();
79  }
80
81  double OneDimensional::variance(void) const
82  {
83    return ap_.y_averager().variance();
84  }
85
86}}} // of namespaces regression, yat, and theplu
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