source:branches/0.4-stable/yat/regression/Linear.cc@1392

Last change on this file since 1392 was 1392, checked in by Peter, 15 years ago

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1// \$Id: Linear.cc 1392 2008-07-28 19:35:30Z peter \$
2
3/*
4  Copyright (C) 2004, 2005, 2006, 2007 Jari Häkkinen, Peter Johansson
5  Copyright (C) 2008 Peter Johansson
6
7  This file is part of the yat library, http://dev.thep.lu.se/yat
8
9  The yat library is free software; you can redistribute it and/or
10  modify it under the terms of the GNU General Public License as
11  published by the Free Software Foundation; either version 2 of the
12  License, or (at your option) any later version.
13
14  The yat library is distributed in the hope that it will be useful,
15  but WITHOUT ANY WARRANTY; without even the implied warranty of
16  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
17  General Public License for more details.
18
19  You should have received a copy of the GNU General Public License
20  along with this program; if not, write to the Free Software
21  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
22  02111-1307, USA.
23*/
24
25#include "Linear.h"
26#include "yat/statistics/AveragerPair.h"
27#include "yat/utility/VectorBase.h"
28
29namespace theplu {
30namespace yat {
31namespace regression {
32
33  Linear::Linear(void)
34    : OneDimensional(), alpha_(0), alpha_var_(0), beta_(0), beta_var_(0)
35  {
36  }
37
38  Linear::~Linear(void)
39  {
40  }
41
42  double Linear::alpha(void) const
43  {
44    return alpha_;
45  }
46
47  double Linear::alpha_var(void) const
48  {
49    return alpha_var_;
50  }
51
52  double Linear::beta(void) const
53  {
54    return beta_;
55  }
56
57  double Linear::beta_var(void) const
58  {
59    return beta_var_;
60  }
61
62  void Linear::fit(const utility::VectorBase& x, const utility::VectorBase& y)
63  {
64    ap_.reset();
65    for (size_t i=0; i<x.size(); i++)
66      ap_.add(x(i),y(i));
67
68    alpha_ = ap_.y_averager().mean();
69    beta_ = ap_.sum_xy_centered() / ap_.x_averager().sum_xx_centered();
70
71    // calculating deviation between data and model
72    chisq_ = (ap_.y_averager().sum_xx_centered() - ap_.sum_xy_centered()*
73              ap_.sum_xy_centered()/ap_.x_averager().sum_xx_centered() );
74    alpha_var_ = s2() / x.size();
75    beta_var_ = s2() / ap_.x_averager().sum_xx_centered();
76  }
77
78  double Linear::predict(const double x) const
79  {
80    return alpha_ + beta_ * (x - ap_.x_averager().mean());
81  }
82
83  double Linear::s2(void) const
84  {
85    return chisq()/(ap_.n()-2);
86  }
87
88  double Linear::standard_error2(const double x) const
89  {
90    return alpha_var_+beta_var_*(x-ap_.x_averager().mean())*
91      (x-ap_.x_averager().mean());
92  }
93
94}}} // of namespaces regression, yat, and theplu
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