source: trunk/yat/regression/MultiDimensional.h @ 1486

Last change on this file since 1486 was 1486, checked in by Jari Häkkinen, 13 years ago

Addresses #436.

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id
File size: 2.6 KB
Line 
1#ifndef _theplu_yat_regression_multidimensional_
2#define _theplu_yat_regression_multidimensional_
3
4// $Id: MultiDimensional.h 1486 2008-09-09 21:17:19Z 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://dev.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 3 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       Number of rows in \a X must match size of \a y.
64
65       \throw A GSL_error exception is thrown if memory allocation
66       fails or the underlying GSL calls fails (usually matrix
67       dimension errors).
68    */
69    void fit(const utility::Matrix& X, const utility::VectorBase& y);
70
71    ///
72    /// @return parameters of the model
73    ///
74    const utility::Vector& fit_parameters(void) const;
75
76    /**
77       @brief Summed Squared Error
78     */
79    double chisq(void) const;
80
81    ///
82    /// @return value in @a x according to fitted model
83    ///
84    double predict(const utility::VectorBase& x) const;
85
86    ///
87    /// @return expected squared prediction error for a new data point
88    /// in @a x
89    ///
90    double prediction_error2(const utility::VectorBase& x) const;
91
92    ///
93    /// @return squared error of model value in @a x
94    ///
95    double standard_error2(const utility::VectorBase& x) const;
96
97  private:
98    double chisquare_;
99    double s2_;
100    utility::Matrix covariance_;
101    utility::Vector fit_parameters_;
102    gsl_multifit_linear_workspace* work_;
103
104  };
105
106}}} // of namespaces regression, yat, and theplu
107
108#endif
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