source: trunk/src/RegressionLocal.h @ 221

// $Id: RegressionLocal.h 221 2004-12-30 22:36:25Z peter $

#ifndef _theplu_statistics_regression_local_
#define _theplu_statistics_regression_local_

// C++ tools include
/////////////////////
#include "Regression.h"
#include "RegressionKernel.h"
#include "vector.h"

// Standard C++ includes
////////////////////////


namespace theplu {
namespace statistics {  
  
  
  ///
  /// Class for Locally-weighted regression.   
  ///
  
  class RegressionLocal 
  {
  
  public:
    ///
    /// Default Constructor.
    ///
    RegressionLocal(void);

    ///
    /// Constructor loading the object with data, type of regressor,
    /// type of kernel and in how many points to predict.
    ///
    RegressionLocal(const gslapi::vector& x, const gslapi::vector& y,
                    Regression& r, RegressionKernel& k, const size_t);

    ///
    /// Copy Constructor. (Not implemented)
    ///
    RegressionLocal(const RegressionLocal&);

    ///
    /// Destructor 
    ///
    virtual ~RegressionLocal(void) {};

    ///
    /// Function returning the points where to predict
    ///
    inline gslapi::vector estimated_x(void) const { return estimated_x_; }

    ///
    /// Function returning predicted values
    ///
    inline gslapi::vector estimated_y(void) const { return estimated_y_; }

    ///
    /// Function returning error of predictions
    ///
    inline gslapi::vector estimated_y_err(void) const {return estimated_y_err_;}
  
    ///
    /// Function performing the fit, using a \a fraction of the data
    /// point and regression method defined in the constructor. The
    /// algorithm uses equally many points around the point to
    /// predict. If this is not possible (because the point is too far
    /// left/right) the points to the extreme left/right is used.
    ///
    void fit(const double fraction);
    
         
  private:
    std::vector<std::pair<double, double> > data_;
    gslapi::vector data_y_;
    RegressionKernel* kernel_;
    Regression* regression_;
    gslapi::vector estimated_x_;
    gslapi::vector estimated_y_;
    gslapi::vector estimated_y_err_;
    
    
  };

  ///
  /// The output operator for Local Regression Class.
  ///
  std::ostream& operator<< (std::ostream& s, const RegressionLocal&);

}} // of namespace statistics and namespace theplu

#endif