source: trunk/yat/regression/PolynomialWeighted.cc

// $Id: PolynomialWeighted.cc 4293 2023-02-04 04:58:12Z peter $

/*
  Copyright (C) 2006, 2007, 2008 Jari Häkkinen, Peter Johansson
  Copyright (C) 2012, 2022 Peter Johansson

  This file is part of the yat library, http://dev.thep.lu.se/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 3 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 yat. If not, see <http://www.gnu.org/licenses/>.
*/

#include <config.h>

#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::VectorBase& x,
                               const utility::VectorBase& y,
                               const utility::VectorBase& 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.
    utility::Vector dummy(x.size(), 1.0);
    add(ap_,x.begin(), x.end(),y.begin(),dummy.begin(),w.begin());
    utility::Matrix X(x.size(), power_+1, 1);
    for (size_t i=0; i<X.rows(); ++i)
      for (size_t 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) 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