source: trunk/yat/regression/Naive.h @ 703

#ifndef _theplu_yat_regression_naive_
#define _theplu_yat_regression_naive_

// $Id: Naive.h 703 2006-12-18 00:47:44Z jari $

/*
  Copyright (C) The authors contributing to this file.

  This file is part of the yat library, http://lev.thep.lu.se/trac/yat

  The yat library is free software; you can redistribute it and/or
  modify it under the terms of the GNU General Public License as
  published by the Free Software Foundation; either version 2 of the
  License, or (at your option) any later version.

  The yat library is distributed in the hope that it will be useful,
  but WITHOUT ANY WARRANTY; without even the implied warranty of
  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
  General Public License for more details.

  You should have received a copy of the GNU General Public License
  along with this program; if not, write to the Free Software
  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
  02111-1307, USA.
*/

#include "OneDimensional.h"

#include <iostream>
#include <utility>

namespace theplu {
namespace yat {
  namespace utility {
    class vector;
  }
namespace regression {

  ///
  /// @bief naive fitting.
  ///
  /// @todo document
  ///
  class Naive : public OneDimensional 
  {
  
  public:
    ///
    /// @brief The default constructor
    ///
    Naive(void);

    ///
    /// @brief The destructor 
    ///
    virtual ~Naive(void);
         
    ///
    /// This function computes the best-fit for the naive model \f$ y
    /// = m \f$ from vectors \a x and \a y, by minimizing \f$
    /// \sum{(y_i-m)^2} \f$. This function is the same as using the
    /// weighted version with unity weights.
    ///
    void fit(const utility::vector& x, const utility::vector& y);

    ///
    /// @brief Mean Squared Error
    ///
    inline double mse(void) const { return mse_; }

    ///
    /// Function predicting value using the naive model. 
    ///
    double predict(const double x) const;
  
    ///
    /// @return standard error
    ///
    double standard_error(const double x) const;

  private:
    ///
    /// @brief The copy constructor (not implemented).
    ///
    Naive(const Naive&);

    double mse_;
  };

}}} // of namespaces regression, yat, and theplu

#endif