STK_MultiLeastSquare.h

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/*--------------------------------------------------------------------*/
/*     Copyright (C) 2004-2016  Serge Iovleff, Université Lille 1, Inria
 
    This program is free software; you can redistribute it and/or modify
    it under the terms of the GNU Lesser General Public License as
    published by the Free Software Foundation; either version 2 of the
    License, or (at your option) any later version.
 
    This program 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 Lesser General Public License for more details.
 
    You should have received a copy of the GNU Lesser 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
 
    Contact : S..._Dot_I..._At_stkpp_Dot_org (see copyright for ...)
*/
 
/*
 * Project:  stkpp::Algebra
 * created on: 1 avr. 2015
 * Author:   iovleff, S..._Dot_I..._At_stkpp_Dot_org (see copyright for ...)
 **/
 
#ifndef STK_MULTILEASTSQUARE_H
#define STK_MULTILEASTSQUARE_H
 
#include "STK_ILeastSquare.h"
#include "STK_SymEigen.h"
#include "Arrays/include/STK_CArraySquare.h"
 
namespace STK
{
// forward declaration
template<class ArrayB, class ArrayA> class MultiLeastSquare;
namespace hidden
{
template<class ArrayB_, class ArrayA_>
struct AlgebraTraits< MultiLeastSquare<ArrayB_, ArrayA_> >
{
  typedef ArrayA_ ArrayA;
  typedef ArrayB_ ArrayB;
};
 
} // namespace hidden
 
template<class ArrayB, class ArrayA>
class MultiLeastSquare: public ILeastSquare<MultiLeastSquare<ArrayB, ArrayA> >
{
  public:
    typedef ILeastSquare<MultiLeastSquare<ArrayB, ArrayA> > Base;
    using Base::b_;
    using Base::a_;
    using Base::x_;
    using Base::rank_;
    inline MultiLeastSquare( ArrayB const& b, ArrayA const& a, bool isBref=false, bool isAref=false)
                          : Base(b, a, isBref, isAref) {}
    inline virtual ~MultiLeastSquare() {};
    bool runImpl();
    template<class Weights>
    bool runImpl(Weights const& weights);
};
 
template<class ArrayB, class ArrayA>
bool MultiLeastSquare<ArrayB, ArrayA>::runImpl()
{
  // compute a'a
  ArraySquareX prod = a_.transpose() * a_;
  // compute (a'a)^{-1}
  SymEigen<ArraySquareX> decomp(prod);
  decomp.run();
  rank_ = decomp.rank();
  // compute (a'a)^{-1}b'a
  if (a_.sizeRows() < b_.sizeCols())
  { x_ = (decomp.ginv(prod) * a_.transpose()) * b_;}
  else
  { x_ = decomp.ginv(prod) * (a_.transpose() * b_);}
  return true;
}
 
/* compute the weighted multidimensional regression */
template<class ArrayB, class ArrayA>
template<class Weights>
bool MultiLeastSquare<ArrayB, ArrayA>::runImpl(Weights const& weights)
{
  STK_STATIC_ASSERT_ONE_DIMENSION_ONLY(Weights);
  // compute a'a
  CSquareX prod = a_.transpose() * weights.diagonalize() * a_;
  // compute (a'a)^{-1}
  SymEigen<CSquareX> decomp(prod);
  decomp.run();
  rank_ = decomp.rank();
  // compute (a'a)^{-1}b'a
  if (a_.sizeRows() < b_.sizeCols())
  { x_ = (decomp.ginv(prod) * a_.transpose())  * weights.diagonalize() * b_;}
  else
  { x_ = decomp.ginv(prod) * (a_.transpose() * weights.diagonalize() * b_);}
  return true;
}
 
} // namespace STK
#endif /* STK_MULTILEASTSQUARE_H */