source: trunk/yat/statistics/OneDimensional.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 Author Date Id Revision
File size: 2.3 KB
Line 
1#ifndef _theplu_yat_regression_onedimensional_
2#define _theplu_yat_regression_onedimensional_
3
4// $Id: OneDimensional.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 "AveragerPair.h"
28
29#include <ostream>
30
31namespace theplu {
32namespace yat {
33namespace utility {
34  class vector;
35}
36namespace regression {
37 
38  ///
39  /// Abstract Base Class for One Dimensional fitting.   
40  ///
41  /// @todo document
42  ///
43  class OneDimensional
44  {
45 
46  public:
47    ///
48    /// Default Constructor.
49    ///
50    inline OneDimensional(void) {}
51
52    ///
53    /// Destructor
54    ///
55    virtual ~OneDimensional(void) {};
56         
57    ///
58    /// This function computes the best-fit given a model (see
59    /// specific class for details) by minimizing \f$
60    /// \sum{(\hat{y_i}-y_i)^2} \f$, where \f$ \hat{y} \f$ is the fitted value.
61    ///
62    virtual void fit(const utility::vector& x, const utility::vector& y)=0; 
63   
64    ///
65    /// function predicting in one point
66    ///
67    virtual double predict(const double x) const=0;
68
69    ///
70    /// @return expected prediction error for a new data point in @a x
71    ///
72    virtual double prediction_error(const double x) const=0;
73
74    ///
75    /// @brief print output to @a os
76    ///
77    std::ostream& print(std::ostream& os,const double min, 
78                        double max, const u_int n) const;
79
80    ///
81    /// @return error of model value in @a x
82    ///
83    virtual double standard_error(const double x) const=0;
84
85  protected:
86    ///
87    /// Averager for pair of x and y
88    ///
89    AveragerPair ap_;
90
91    ///
92    /// mean squared deviation (model from data points)
93    ///
94    double msd_; 
95  };
96
97}}} // of namespaces regression, yat, and theplu
98
99#endif
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