source: trunk/c++_tools/statistics/MultiDimensional.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_
2#define _theplu_statistics_regression_multidimensional_
3
4// $Id: MultiDimensional.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 MultiDimensional
41  {
42  public:
43
44    ///
45    /// @brief Default Constructor
46    ///
47    inline MultiDimensional(void) : chisquare_(0), work_(NULL) {}
48
49    ///
50    /// @brief Destructor
51    ///
52    inline ~MultiDimensional(void) { if (work_) gsl_multifit_linear_free(work_);}
53
54    ///
55    /// Function fitting parameters of the linear model by miminizing
56    /// the quadratic deviation between model and data.
57    ///
58    void fit(const utility::matrix& X, const utility::vector& y);
59
60    ///
61    /// @return parameters of the model
62    ///
63    utility::vector fit_parameters(void) { return fit_parameters_; }
64
65    ///
66    /// @return value in @a x according to fitted model
67    ///
68    inline double predict(const utility::vector& x) const 
69    { return fit_parameters_ * x; }
70
71    ///
72    /// @return expected prediction error for a new data point in @a x
73    ///
74    double prediction_error(const utility::vector& x) const;
75
76    ///
77    /// @return error of model value in @a x
78    ///
79    double standard_error(const utility::vector& x) const;
80
81  private:
82    double chisquare_;
83    utility::matrix covariance_;
84    utility::vector fit_parameters_;
85    gsl_multifit_linear_workspace* work_;
86
87  };
88
89
90}}} // of namespaces regression, statisitcs and thep
91
92#endif
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