dynare/mex/sources/estimation/LogLikelihoodMain.hh

78 lines
3.3 KiB
C++

/*
* Copyright (C) 2009-2013 Dynare Team
*
* This file is part of Dynare.
*
* Dynare 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.
*
* Dynare 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 Dynare. If not, see <http://www.gnu.org/licenses/>.
*/
///////////////////////////////////////////////////////////
// LogLikelihoodMain.h
// Implementation of the Class LogLikelihoodMain
// Created on: 02-Feb-2010 12:57:09
///////////////////////////////////////////////////////////
#if !defined(E126AEF5_AC28_400a_821A_3BCFD1BC4C22__INCLUDED_)
#define E126AEF5_AC28_400a_821A_3BCFD1BC4C22__INCLUDED_
#include "LogLikelihoodSubSample.hh"
class LogLikelihoodMain
{
private:
std::vector<EstimationSubsample> &estSubsamples; // reference to member of EstimatedParametersDescription
LogLikelihoodSubSample logLikelihoodSubSample;
Vector vll; // vector of all KF step likelihoods
Matrix detrendedData;
public:
virtual ~LogLikelihoodMain();
LogLikelihoodMain(const std::string &basename, EstimatedParametersDescription &estiParDesc, size_t n_endo, size_t n_exo,
const std::vector<size_t> &zeta_fwrd_arg, const std::vector<size_t> &zeta_back_arg, const std::vector<size_t> &zeta_mixed_arg,
const std::vector<size_t> &zeta_static_arg, const double qz_criterium_arg, const std::vector<size_t> &varobs_arg,
double riccati_tol_arg, double lyapunov_tol_arg,
bool noconstant_arg);
/**
* Compute method Inputs:
* Matrix &steadyState; Matrix of sub-sample periods column-vectors of steady states, one column vectro for each sub-sample period
* vectors of deep deepParams and estimated estParams
* Matrix &data input data reference
* Q and H KF matrices of shock and measurement error varinaces and covariances
* KF logLikelihood calculation start period.
*/
template <class VEC1, class VEC2>
double compute(VEC1 &steadyState, VEC2 &estParams, VectorView &deepParams, const MatrixConstView &data,
MatrixView &Q, Matrix &H, size_t start)
{
double logLikelihood = 0;
for (size_t i = 0; i < estSubsamples.size(); ++i)
{
MatrixConstView dataView(data, 0, estSubsamples[i].startPeriod,
data.getRows(), estSubsamples[i].endPeriod-estSubsamples[i].startPeriod+1);
MatrixView detrendedDataView(detrendedData, 0, estSubsamples[i].startPeriod,
data.getRows(), estSubsamples[i].endPeriod-estSubsamples[i].startPeriod+1);
VectorView vllView(vll, estSubsamples[i].startPeriod, estSubsamples[i].endPeriod-estSubsamples[i].startPeriod+1);
logLikelihood += logLikelihoodSubSample.compute(steadyState, dataView, estParams, deepParams,
Q, H, vllView, detrendedDataView, start, i);
}
return logLikelihood;
};
Vector &getVll() { return vll; };
};
#endif // !defined(E126AEF5_AC28_400a_821A_3BCFD1BC4C22__INCLUDED_)