source: trunk/yat/regression/MultiDimensional.cc @ 1275

Last change on this file since 1275 was 1275, checked in by Jari Häkkinen, 13 years ago

Updating copyright statements.

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id
File size: 2.9 KB
Line 
1// $Id: MultiDimensional.cc 1275 2008-04-11 06:10:12Z jari $
2
3/*
4  Copyright (C) 2005 Jari Häkkinen
5  Copyright (C) 2006, 2007, 2008 Jari Häkkinen, Peter Johansson
6
7  This file is part of the yat library, http://trac.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 "MultiDimensional.h"
26#include "yat/utility/Exception.h"
27#include "yat/utility/Matrix.h"
28#include "yat/utility/VectorBase.h"
29#include "yat/utility/Vector.h"
30
31#include <cassert>
32
33namespace theplu {
34namespace yat {
35namespace regression {
36
37
38  MultiDimensional::MultiDimensional(void)
39    : chisquare_(0), work_(NULL)
40  {
41  }
42
43
44  MultiDimensional::~MultiDimensional(void)
45  {
46    if (work_)
47      gsl_multifit_linear_free(work_);
48  }
49
50
51  const utility::Matrix& MultiDimensional::covariance(void) const
52  {
53    return covariance_;
54  }
55
56
57  void MultiDimensional::fit(const utility::Matrix& x, 
58                             const utility::VectorBase& y)
59  {
60    assert(x.rows()==y.size());
61    covariance_.resize(x.columns(),x.columns());
62    fit_parameters_ = utility::Vector(x.columns());
63    if (work_)
64      gsl_multifit_linear_free(work_);
65    if (!(work_=gsl_multifit_linear_alloc(x.rows(),fit_parameters_.size())))
66      throw utility::GSL_error("MultiDimensional::fit failed to allocate memory");
67
68    int status = gsl_multifit_linear(x.gsl_matrix_p(), y.gsl_vector_p(),
69                                     fit_parameters_.gsl_vector_p(),
70                                     covariance_.gsl_matrix_p(), &chisquare_,
71                                     work_);
72    if (status)
73      throw utility::GSL_error(std::string("MultiDimensional::fit",status));
74
75    s2_ = chisquare_/(x.rows()-x.columns());
76  }
77
78  const utility::Vector& MultiDimensional::fit_parameters(void) const
79  { 
80    return fit_parameters_; 
81  }
82
83
84  double MultiDimensional::chisq(void) const
85  {
86    return chisquare_;
87  }
88
89
90  double MultiDimensional::predict(const utility::VectorBase& x) const 
91  {
92    assert(x.size()==fit_parameters_.size());
93    return fit_parameters_ * x;
94  }
95
96
97  double MultiDimensional::prediction_error2(const utility::VectorBase& x) const
98  {
99    return standard_error2(x) + s2_;
100  }
101
102
103  double MultiDimensional::standard_error2(const utility::VectorBase& x) const
104  {
105    double s2 = 0;
106    for (size_t i=0; i<x.size(); ++i){
107      s2 += covariance_(i,i)*x(i)*x(i);
108      for (size_t j=i+1; j<x.size(); ++j)
109        s2 += 2*covariance_(i,j)*x(i)*x(j);
110    }
111    return s2;
112  }
113
114}}} // of namespaces regression, yat, and theplu
Note: See TracBrowser for help on using the repository browser.