source: trunk/yat/regression/PolynomialWeighted.cc @ 1797

Last change on this file since 1797 was 1797, checked in by Peter, 13 years ago

updating copyright statements

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1// $Id: PolynomialWeighted.cc 1797 2009-02-12 18:07:10Z peter $
2
3/*
4  Copyright (C) 2006, 2007, 2008 Jari Häkkinen, Peter Johansson
5
6  This file is part of the yat library, http://dev.thep.lu.se/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 3 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 yat. If not, see <http://www.gnu.org/licenses/>.
20*/
21
22#include "PolynomialWeighted.h"
23#include "yat/utility/Matrix.h"
24#include "yat/utility/Vector.h"
25
26#include <cassert>
27
28namespace theplu {
29namespace yat {
30namespace regression {
31
32  PolynomialWeighted::PolynomialWeighted(size_t power)
33    : OneDimensionalWeighted(), power_(power)
34  {
35  }
36
37  PolynomialWeighted::~PolynomialWeighted(void)
38  {
39  }
40
41  void PolynomialWeighted::fit(const utility::VectorBase& x,
42                               const utility::VectorBase& y,
43                               const utility::VectorBase& w)
44  {
45    assert(x.size()==y.size());
46    assert(y.size()==w.size());
47    ap_.reset();
48    // AveragerPairWeighted requires 2 weights but works only on the
49    // product wx*wy, so we can send in w and a dummie to get what we
50    // want.
51    utility::Vector dummy(x.size(), 1.0);
52    add(ap_,x.begin(), x.end(),y.begin(),dummy.begin(),w.begin());
53    utility::Matrix X=utility::Matrix(x.size(),power_+1,1);
54    for (size_t i=0; i<X.rows(); ++i)
55      for (size_t j=1; j<X.columns(); ++j)
56        X(i,j)=X(i,j-1)*x(i);
57    md_.fit(X,y,w);
58    chisq_=md_.chisq();
59  }
60
61
62  const utility::Vector& PolynomialWeighted::fit_parameters(void) const
63  {
64    return md_.fit_parameters(); 
65  }
66
67
68  double PolynomialWeighted::s2(const double w) const
69  {
70    return md_.s2(w);
71  }
72
73  double PolynomialWeighted::predict(const double x) const
74  {
75    utility::Vector vec(power_+1,1);
76    for (size_t i=1; i<=power_; ++i)
77      vec(i) = vec(i-1)*x;
78    return md_.predict(vec);
79  }
80
81  double PolynomialWeighted::standard_error2(const double x) const
82  {
83    utility::Vector vec(power_+1,1);
84    for (size_t i=1; i<=power_; ++i)
85      vec(i) = vec(i-1)*x;
86    return md_.standard_error2(vec);
87  }
88
89}}} // of namespaces regression, yat, and theplu
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