source: trunk/lib/statistics/Local.h @ 430

// $Id: Local.h 430 2005-12-08 22:53:08Z peter $

#ifndef _theplu_statistics_regression_local_
#define _theplu_statistics_regression_local_

#include <c++_tools/statistics/Kernel.h>
#include <c++_tools/statistics/OneDimensionalWeighted.h>
#include <c++_tools/gslapi/vector.h>

#include <iostream>

namespace theplu {
namespace statistics {
namespace regression {

  ///
  /// Class for Locally weighted regression. 
  ///
  /// Locally weighted regression is an algorithm for learning
  /// continuous non-linear mappings in a non-parametric manner.  In
  /// locally weighted regression, points are weighted by proximity to
  /// the current x in question using a Kernel. A weighted regression
  /// is then computed using the weighted points and a specific
  /// Regression method. This procedure is repeated, which results in
  /// a pointwise approximation of the underlying (unknown) function.
  ///
  class Local
  {
  
  public:
    ///
    /// Constructor taking type of \a regressor,
    /// type of \a kernel.
    ///
    inline Local(OneDimensionalWeighted& r, Kernel& k) 
      : kernel_(&k), regressor_(&r) {}

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


    ///
    /// adding a data point
    ///
    inline void add(const double x, const double y) 
    { data_.push_back(std::make_pair(x,y)); }

    ///
    /// Function returning predicted values
    ///
    inline const gslapi::vector& y_predicted(void) const 
    { return y_predicted_; }

    ///
    /// Function returning error of predictions
    ///
    inline const gslapi::vector& y_err(void) const { return y_err_; }
  
    ///
    /// Performs the fit in data defined by add using a
    /// RegressionKernel and a Regression method defined in the
    /// constructor. For each element in vector \a x a fit is
    /// performed. The kernel used has width \a width and is
    /// centralized over the data point \f$ x_i \f$, which means data
    /// in \f$ [x-width, x+width] is used in the fit.
    ///
    void fit(const double width, const gslapi::vector& x);

    ///
    /// @return x-values where fitting was performed.
    ///
    inline const gslapi::vector& x(void) const { return x_; }

  private:
    ///
    /// Copy Constructor. (Not implemented)
    ///
    Local(const Local&);

    std::vector<std::pair<double, double> > data_;
    Kernel* kernel_;
    OneDimensionalWeighted* regressor_;
    gslapi::vector x_;
    gslapi::vector y_predicted_; 
    gslapi::vector y_err_; 

  };

  ///
  /// The output operator for the RegressionLocal class.
  ///
  std::ostream& operator<<(std::ostream&, const Local& );


}}} // of namespaces regression, statistics and thep

#endif