source: trunk/yat/regression/Polynomial.h @ 713

Last change on this file since 713 was 713, checked in by Peter, 16 years ago

Fixes #77, #78, #158, and #163, and refs #81

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id
File size: 2.2 KB
Line 
1#ifndef _theplu_yat_regression_polynomial_
2#define _theplu_yat_regression_polynomial_
3
4// $Id: Polynomial.h 713 2006-12-21 14:43:31Z peter $
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 "OneDimensional.h"
28#include "MultiDimensional.h"
29#include "yat/utility/vector.h"
30
31#include <gsl/gsl_multifit.h>
32
33#include <cassert>
34
35namespace theplu {
36namespace yat {
37namespace regression {
38
39  /**
40     @brief Polynomial regression
41     
42     Data are modeled as \f$ y = \alpha + \beta x + \gamma x^2 +
43     ... + \delta x_i^{\textrm{power}} + \epsilon_i \f$
44  */
45  class Polynomial : public OneDimensional
46  {
47  public:
48
49    ///
50    /// @param power degree of polynomial, e.g. 1 for a linear model
51    ///
52    explicit Polynomial(size_t power);
53
54    ///
55    /// @brief Destructor
56    ///
57    ~Polynomial(void);
58
59    ///
60    /// Fit the model by minimizing the mean squared deviation between
61    /// model and data.
62    ///
63    void fit(const utility::vector& x, const utility::vector& y);
64
65    ///
66    /// @return parameters of the model
67    ///
68    /// @see MultiDimensional
69    ///
70    const utility::vector& fit_parameters(void) const;
71
72    ///
73    /// @brief Variance of residuals
74    ///
75    double chisq(void) const;
76
77    ///
78    /// @return value in @a x of model
79    ///
80    double predict(const double x) const;
81
82    ///
83    /// @return error of model value in @a x
84    ///
85    double standard_error(const double x) const;
86
87  private:
88    MultiDimensional md_;
89    size_t power_;
90
91  };
92
93}}} // of namespaces regression, yat, and theplu
94
95#endif
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