source: trunk/yat/statistics/MultiDimensionalWeighted.h @ 681

Last change on this file since 681 was 681, checked in by Jari Häkkinen, 16 years ago

Moved namespace regression up one level (leaving namespace statistics).

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id
File size: 2.3 KB
Line 
1#ifndef _theplu_yat_regression_multidimensionalweighted_
2#define _theplu_yat_regression_multidimensionalweighted_
3
4// $Id: MultiDimensionalWeighted.h 681 2006-10-11 21:38:46Z 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
32namespace theplu {
33namespace yat {
34namespace regression {
35
36  ///
37  /// @brief MultiDimesional fitting.
38  ///
39  class MultiDimensionalWeighted
40  {
41  public:
42
43    ///
44    /// @brief Default Constructor
45    ///
46    inline MultiDimensionalWeighted(void) : chisquare_(0), work_(NULL) {}
47
48    ///
49    /// @brief Destructor
50    ///
51    inline ~MultiDimensionalWeighted(void) 
52    { if (work_) gsl_multifit_linear_free(work_);}
53
54    ///
55    /// @see gsl_multifit_wlinear
56    ///
57    void fit(const utility::matrix& X, const utility::vector& y, 
58             const utility::vector& w);
59
60    ///
61    /// @return value in @a x according to fitted model
62    ///
63    inline double predict(const utility::vector& x) const 
64    { return fit_parameters_ * x; }
65
66    ///
67    /// @return expected prediction error for a new data point in @a x
68    ///
69    double prediction_error(const utility::vector& x, const double w) const;
70
71    ///
72    /// @return error of model value in @a x
73    ///
74    double standard_error(const utility::vector& x) const;
75
76    ///
77    /// @return parameters of fitted model
78    ///
79    utility::vector fit_parameters(void) { return fit_parameters_; }
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}}} // of namespaces regression, yat, and theplu
90
91#endif
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