source: trunk/yat/regression/PolynomialWeighted.cc @ 741

// $Id: PolynomialWeighted.cc 741 2007-01-13 14:41:40Z peter $

/*
  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 "PolynomialWeighted.h"
#include "yat/utility/matrix.h"
#include "yat/utility/vector.h"

#include <cassert>

namespace theplu {
namespace yat {
namespace regression {

  PolynomialWeighted::PolynomialWeighted(size_t power)
    : OneDimensionalWeighted(), power_(power)
  {
  }

  PolynomialWeighted::~PolynomialWeighted(void)
  {
  }

  void PolynomialWeighted::fit(const utility::vector& x,
                               const utility::vector& y,
                               const utility::vector& w)
  {
    assert(x.size()==y.size());
    assert(y.size()==w.size());
    ap_.reset();
    // AveragerPairWeighted requires 2 weights but works only on the
    // product wx*wy, so we can send in w and a dummie to get what we
    // want.
    ap_.add_values(x,y,utility::vector(x.size(),1),w);
    utility::matrix X=utility::matrix(x.size(),power_+1,1);
    for (size_t i=0; i<X.rows(); ++i)
      for (u_int j=1; j<X.columns(); j++)
        X(i,j)=X(i,j-1)*x(i);
    md_.fit(X,y,w);
    chisq_=md_.chisq();
  }


  const utility::vector& PolynomialWeighted::fit_parameters(void) const
  {
    return md_.fit_parameters(); 
  }


  double PolynomialWeighted::s2(const double w=1.0) const
  {
    return md_.s2(w);
  }

  double PolynomialWeighted::predict(const double x) const
  {
    utility::vector vec(power_+1,1);
    for (size_t i=1; i<=power_; ++i)
      vec(i) = vec(i-1)*x;
    return md_.predict(vec);
  }

  double PolynomialWeighted::standard_error2(const double x) const
  {
    utility::vector vec(power_+1,1);
    for (size_t i=1; i<=power_; ++i)
      vec(i) = vec(i-1)*x;
    return md_.standard_error2(vec);
  }

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