source: trunk/yat/regression/PolynomialWeighted.cc @ 741

Last change on this file since 741 was 741, checked in by Peter, 15 years ago

fixes #161 and #164

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id
File size: 2.4 KB
Line 
1// $Id: PolynomialWeighted.cc 741 2007-01-13 14:41:40Z 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 "PolynomialWeighted.h"
25#include "yat/utility/matrix.h"
26#include "yat/utility/vector.h"
27
28#include <cassert>
29
30namespace theplu {
31namespace yat {
32namespace regression {
33
34  PolynomialWeighted::PolynomialWeighted(size_t power)
35    : OneDimensionalWeighted(), power_(power)
36  {
37  }
38
39  PolynomialWeighted::~PolynomialWeighted(void)
40  {
41  }
42
43  void PolynomialWeighted::fit(const utility::vector& x,
44                               const utility::vector& y,
45                               const utility::vector& w)
46  {
47    assert(x.size()==y.size());
48    assert(y.size()==w.size());
49    ap_.reset();
50    // AveragerPairWeighted requires 2 weights but works only on the
51    // product wx*wy, so we can send in w and a dummie to get what we
52    // want.
53    ap_.add_values(x,y,utility::vector(x.size(),1),w);
54    utility::matrix X=utility::matrix(x.size(),power_+1,1);
55    for (size_t i=0; i<X.rows(); ++i)
56      for (u_int j=1; j<X.columns(); j++)
57        X(i,j)=X(i,j-1)*x(i);
58    md_.fit(X,y,w);
59    chisq_=md_.chisq();
60  }
61
62
63  const utility::vector& PolynomialWeighted::fit_parameters(void) const
64  {
65    return md_.fit_parameters(); 
66  }
67
68
69  double PolynomialWeighted::s2(const double w=1.0) const
70  {
71    return md_.s2(w);
72  }
73
74  double PolynomialWeighted::predict(const double x) const
75  {
76    utility::vector vec(power_+1,1);
77    for (size_t i=1; i<=power_; ++i)
78      vec(i) = vec(i-1)*x;
79    return md_.predict(vec);
80  }
81
82  double PolynomialWeighted::standard_error2(const double x) const
83  {
84    utility::vector vec(power_+1,1);
85    for (size_t i=1; i<=power_; ++i)
86      vec(i) = vec(i-1)*x;
87    return md_.standard_error2(vec);
88  }
89
90}}} // of namespaces regression, yat, and theplu
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