source: trunk/yat/regression/MultiDimensionalWeighted.h

Last change on this file was 2127, checked in by Peter, 12 years ago

fixes #566

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id
File size: 2.6 KB
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1#ifndef _theplu_yat_regression_multidimensionalweighted_
2#define _theplu_yat_regression_multidimensionalweighted_
3
4// $Id: MultiDimensionalWeighted.h 2127 2009-12-22 20:45:22Z peter $
5
6/*
7  Copyright (C) 2006, 2007, 2008 Jari Häkkinen, Peter Johansson
8  Copyright (C) 2009 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 yat. If not, see <http://www.gnu.org/licenses/>.
24*/
25
26#include "yat/utility/Matrix.h"
27#include "yat/utility/Vector.h"
28
29#include <gsl/gsl_multifit.h>
30
31namespace theplu {
32namespace yat {
33namespace regression {
34
35  ///
36  /// @brief MultiDimesional fitting.
37  ///
38  class MultiDimensionalWeighted
39  {
40  public:
41
42    ///
43    /// @brief Default Constructor
44    ///
45    MultiDimensionalWeighted(void);
46
47    ///
48    /// @brief Destructor
49    ///
50    ~MultiDimensionalWeighted(void);
51
52    ///
53    /// @return sum of squared residuals
54    ///
55    double chisq(void) const;
56
57    /**
58       \see gsl_multifit_wlinear
59
60       \throw A GSL_error exception is thrown if memory allocation
61       fails or the underlying GSL calls fails (usually matrix
62       dimension errors).
63    */
64    void fit(const utility::Matrix& X, const utility::VectorBase& y, 
65             const utility::VectorBase& w);
66
67    ///
68    /// @return value in @a x according to fitted model
69    ///
70    double predict(const utility::VectorBase& x) const;
71
72    ///
73    /// @return expected squared prediction error for a new data point
74    /// in @a x
75    ///
76    double prediction_error2(const utility::VectorBase& x, 
77                             const double w=1) const;
78
79    ///
80    /// @return error of model value in @a x
81    ///
82    double standard_error2(const utility::VectorBase& x) const;
83
84    ///
85    /// @return parameters of fitted model
86    ///
87    const utility::Vector& fit_parameters(void) const;
88
89    ///
90    /// @return variance of residuals
91    ///
92    double s2(const double w=1.0) const;
93
94  private:
95    // no copy allowed
96    MultiDimensionalWeighted(const MultiDimensionalWeighted&);
97    MultiDimensionalWeighted& operator=(const MultiDimensionalWeighted&);
98
99    double chisquare_;
100    utility::Matrix covariance_;
101    utility::Vector fit_parameters_;
102    double s2_;
103    gsl_multifit_linear_workspace* work_;
104
105  };
106
107}}} // of namespaces regression, yat, and theplu
108
109#endif
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