# source:trunk/src/RegressionNaive.h@216

Last change on this file since 216 was 216, checked in by Peter, 18 years ago

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1// $Id: RegressionNaive.h 216 2004-12-29 09:29:54Z peter$
2
3#ifndef _theplu_statistics_regression_linear_
4#define _theplu_statistics_regression_linear_
5
6// C++ tools include
7/////////////////////
8#include "Averager.h"
9#include "Regression.h"
10#include "vector.h"
11#include "WeightedAverager.h"
12// Standard C++ includes
13////////////////////////
14#include <gsl/gsl_fit.h>
15#include <utility>
16
17namespace theplu {
18namespace statistics {
19
20  ///
21  /// Class for Regression.
22  ///
23
24
25  class RegressionNaive : public Regression
26  {
27
28  public:
29    ///
30    /// Default Constructor.
31    ///
32    RegressionNaive(void);
33
34    ///
35    /// Copy Constructor. (not implemented)
36    ///
37    RegressionNaive(const RegressionNaive&);
38
39    ///
40    /// Destructor
41    ///
42    virtual ~RegressionNaive(void) {};
43
44    inline void estimate(const double x, double& y, double& y_err)
45    { y=m_; y_err=sqrt(var_); }
46
47    ///
48    /// This function computes the best-fit for the naive model \f$49 /// y = m \f$ from vectors \a x and \a y, by minimizing \f$50 /// \sum{(y_i-m)^2} \f$.
51    ///
52    inline int fit(const gslapi::vector& x, const gslapi::vector& y)
53    {
54      Averager a;
55      for (size_t i=0; i<y.size(); i++)
57      m_=a.mean();
58      var_=a.standard_error()*a.standard_error();
59      return 0;
60    }
61
62    ///
63    /// This function computes the best-fit for the naive model \f$y 64 /// = m \f$ from vectors \a x and \a y, by minimizing \f$\sum 65 /// w_i(y_i-m)^2 \f$. The weight \f$w_i \f$ is the inverse of the
66    /// variance for \f$y_i \f$
67    ///
68    inline int fit_weighted(const gslapi::vector& x,
69                            const gslapi::vector& y,
70                            const gslapi::vector& w)
71    {
72      WeightedAverager a;
73      for (size_t i=0; i<y.size(); i++)
75      m_=a.mean();
76      var_=a.standard_error()*a.standard_error();
77      return 0;
78    }
79
80
81  private:
82    double var_;
83    double m_;
84
85  };
86
87}} // of namespace statistics and namespace theplu
88
89#endif
90
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