source: trunk/c++_tools/statistics/PolynomialWeighted.cc @ 675

Last change on this file since 675 was 675, checked in by Jari Häkkinen, 15 years ago

References #83. Changing project name to yat. Compilation will fail in this revision.

  • Property svn:eol-style set to native
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1// $Id: PolynomialWeighted.cc 675 2006-10-10 12:08:45Z jari $
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 "yat/statistics/PolynomialWeighted.h"
25#include "yat/utility/matrix.h"
26#include "yat/utility/vector.h"
27
28#include <cassert>
29
30namespace theplu {
31namespace statistics {
32namespace regression {
33
34
35  void PolynomialWeighted::fit(const utility::vector& x,
36                               const utility::vector& y,
37                               const utility::vector& w)
38  {
39    assert(x.size()==y.size());
40    assert(y.size()==w.size());
41    utility::matrix X=utility::matrix(x.size(),power_+1,1);
42    for (size_t i=0; i<X.rows(); ++i)
43      for (u_int j=1; j<X.columns(); j++)
44        X(i,j)=X(i,j-1)*x(i);
45    md_.fit(X,y,w);
46  }
47
48  double PolynomialWeighted::predict(const double x) const
49  {
50    utility::vector vec(power_+1,1);
51    for (size_t i=1; i<=power_; ++i)
52      vec(i) = vec(i-1)*x;
53    return md_.predict(vec);
54  }
55
56  double PolynomialWeighted::prediction_error(const double x, 
57                                              const double w) const
58  {
59    utility::vector vec(power_+1,1);
60    for (size_t i=1; i<=power_; ++i)
61      vec(i) = vec(i-1)*x;
62    return md_.prediction_error(vec, w);
63  }
64
65  double PolynomialWeighted::standard_error(const double x) const
66  {
67    utility::vector vec(power_+1,1);
68    for (size_t i=1; i<=power_; ++i)
69      vec(i) = vec(i-1)*x;
70    return md_.standard_error(vec);
71  }
72
73}}} // of namespaces regression, statisitcs and thep
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