source: trunk/c++_tools/statistics/MultiDimensionalWeighted.h @ 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
  • Property svn:keywords set to Id
File size: 2.3 KB
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1#ifndef _theplu_statistics_regression_multidimensional_weighted_
2#define _theplu_statistics_regression_multidimensional_weighted_
3
4// $Id: MultiDimensionalWeighted.h 675 2006-10-10 12:08:45Z jari $
5
6/*
7  Copyright (C) The authors contributing to this file.
8
9  This file is part of the yat library, http://lev.thep.lu.se/trac/yat
10
11  The yat library is free software; you can redistribute it and/or
12  modify it under the terms of the GNU General Public License as
13  published by the Free Software Foundation; either version 2 of the
14  License, or (at your option) any later version.
15
16  The yat library is distributed in the hope that it will be useful,
17  but WITHOUT ANY WARRANTY; without even the implied warranty of
18  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
19  General Public License for more details.
20
21  You should have received a copy of the GNU General Public License
22  along with this program; if not, write to the Free Software
23  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
24  02111-1307, USA.
25*/
26
27#include "yat/utility/matrix.h"
28#include "yat/utility/vector.h"
29
30#include <gsl/gsl_multifit.h>
31
32
33namespace theplu {
34namespace statistics {
35namespace regression {
36
37  ///
38  /// @brief MultiDimesional fitting.
39  ///
40  class MultiDimensionalWeighted
41  {
42  public:
43
44    ///
45    /// @brief Default Constructor
46    ///
47    inline MultiDimensionalWeighted(void) : chisquare_(0), work_(NULL) {}
48
49    ///
50    /// @brief Destructor
51    ///
52    inline ~MultiDimensionalWeighted(void) 
53    { if (work_) gsl_multifit_linear_free(work_);}
54
55    ///
56    /// @see gsl_multifit_wlinear
57    ///
58    void fit(const utility::matrix& X, const utility::vector& y, 
59             const utility::vector& w);
60
61    ///
62    /// @return value in @a x according to fitted model
63    ///
64    inline double predict(const utility::vector& x) const 
65    { return fit_parameters_ * x; }
66
67    ///
68    /// @return expected prediction error for a new data point in @a x
69    ///
70    double prediction_error(const utility::vector& x, const double w) const;
71
72    ///
73    /// @return error of model value in @a x
74    ///
75    double standard_error(const utility::vector& x) const;
76
77    ///
78    /// @return parameters of fitted model
79    ///
80    utility::vector fit_parameters(void) { return fit_parameters_; }
81
82  private:
83    double chisquare_;
84    utility::matrix covariance_;
85    utility::vector fit_parameters_;
86    gsl_multifit_linear_workspace* work_;
87
88  };
89
90
91}}} // of namespaces regression, statisitcs and thep
92
93#endif
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