source: trunk/yat/regression/MultiDimensional.h @ 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: 2.5 KB
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1#ifndef _theplu_yat_regression_multidimensional_
2#define _theplu_yat_regression_multidimensional_
3
4// $Id: MultiDimensional.h 1275 2008-04-11 06:10:12Z jari $
5
6/*
7  Copyright (C) 2005, 2006, 2007 Jari Häkkinen, Peter Johansson
8  Copyright (C) 2008 Peter Johansson
9
10  This file is part of the yat library, http://trac.thep.lu.se/yat
11
12  The yat library is free software; you can redistribute it and/or
13  modify it under the terms of the GNU General Public License as
14  published by the Free Software Foundation; either version 2 of the
15  License, or (at your option) any later version.
16
17  The yat library is distributed in the hope that it will be useful,
18  but WITHOUT ANY WARRANTY; without even the implied warranty of
19  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
20  General Public License for more details.
21
22  You should have received a copy of the GNU General Public License
23  along with this program; if not, write to the Free Software
24  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
25  02111-1307, USA.
26*/
27
28#include "yat/utility/Matrix.h"
29#include "yat/utility/VectorBase.h"
30
31#include <gsl/gsl_multifit.h>
32
33namespace theplu {
34namespace yat {
35namespace regression {
36
37  ///
38  /// @brief MultiDimesional fitting.
39  ///
40  class MultiDimensional
41  {
42  public:
43
44    ///
45    /// @brief Default Constructor
46    ///
47    MultiDimensional(void);
48
49    ///
50    /// @brief Destructor
51    ///
52    ~MultiDimensional(void);
53
54    ///
55    /// @brief covariance of parameters
56    ///
57    const utility::Matrix& covariance(void) const;
58
59    /**
60       \brief Function fitting parameters of the linear model by
61       miminizing the quadratic deviation between model and data.
62
63       \throw A GSL_error exception is thrown if memory allocation
64       fails or the underlying GSL calls fails (usually matrix
65       dimension errors).
66    */
67    void fit(const utility::Matrix& X, const utility::VectorBase& y);
68
69    ///
70    /// @return parameters of the model
71    ///
72    const utility::Vector& fit_parameters(void) const;
73
74    /**
75       @brief Summed Squared Error
76     */
77    double chisq(void) const;
78
79    ///
80    /// @return value in @a x according to fitted model
81    ///
82    double predict(const utility::VectorBase& x) const;
83
84    ///
85    /// @return expected squared prediction error for a new data point
86    /// in @a x
87    ///
88    double prediction_error2(const utility::VectorBase& x) const;
89
90    ///
91    /// @return squared error of model value in @a x
92    ///
93    double standard_error2(const utility::VectorBase& x) const;
94
95  private:
96    double chisquare_;
97    double s2_;
98    utility::Matrix covariance_;
99    utility::Vector fit_parameters_;
100    gsl_multifit_linear_workspace* work_;
101
102  };
103
104}}} // of namespaces regression, yat, and theplu
105
106#endif
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