121 lines
3.7 KiB
C++
121 lines
3.7 KiB
C++
/*
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* Copyright (C) 2010-2017 Dynare Team
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*
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* This file is part of Dynare.
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*
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* Dynare is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Dynare is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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*/
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///////////////////////////////////////////////////////////
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// RandomWalkMetropolisHastings.hh
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// Implementation of the Class RandomWalkMetropolisHastings
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// Created on: 07-Sep-2010 15:21:40
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///////////////////////////////////////////////////////////
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#if !defined(A6BBC5E0_598E_4863_B7FF_E87320056B80__INCLUDED_)
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#define A6BBC5E0_598E_4863_B7FF_E87320056B80__INCLUDED_
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#include <iostream>
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#include <fstream>
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#include "LogPosteriorDensity.hh"
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#include "Proposal.hh"
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class RandomWalkMetropolisHastings
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{
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private:
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Vector parDraw, newParDraw;
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public:
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RandomWalkMetropolisHastings(size_t size) :
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parDraw(size), newParDraw(size)
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{
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};
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virtual ~RandomWalkMetropolisHastings()
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{
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};
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template<class VEC1>
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double
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compute(VectorView &mhLogPostDens, MatrixView &mhParams, VEC1 &steadyState,
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Vector &estParams, VectorView &deepParams, const MatrixConstView &data, MatrixView &Q, Matrix &H,
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const size_t presampleStart, const size_t startDraw, size_t nMHruns,
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LogPosteriorDensity &lpd, Proposal &pDD, EstimatedParametersDescription &epd)
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{
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//streambuf *likbuf, *drawbuf *backup;
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std::ofstream urandfilestr, drawfilestr;
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urandfilestr.open("urand.csv");
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drawfilestr.open("paramdraws.csv");
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bool overbound;
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double newLogpost, logpost, urand;
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size_t count, accepted = 0;
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parDraw = estParams;
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logpost = -lpd.compute(steadyState, estParams, deepParams, data, Q, H, presampleStart);
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for (size_t run = startDraw - 1; run < nMHruns; ++run)
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{
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overbound = false;
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pDD.draw(parDraw, newParDraw);
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for (count = 0; count < parDraw.getSize(); ++count)
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{
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overbound = (newParDraw(count) < epd.estParams[count].lower_bound || newParDraw(count) > epd.estParams[count].upper_bound);
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if (overbound)
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{
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newLogpost = -INFINITY;
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break;
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}
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}
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if (!overbound)
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{
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try
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{
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newLogpost = -lpd.compute(steadyState, newParDraw, deepParams, data, Q, H, presampleStart);
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}
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catch (const std::exception &e)
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{
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throw; // for now handle the system and other errors higher-up
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}
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catch (...)
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{
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newLogpost = -INFINITY;
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}
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}
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urand = pDD.selectionTestDraw();
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if ((newLogpost > -INFINITY) && log(urand) < newLogpost-logpost)
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{
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parDraw = newParDraw;
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logpost = newLogpost;
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accepted++;
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}
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mat::get_row(mhParams, run) = parDraw;
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mhLogPostDens(run) = logpost;
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urandfilestr << urand << "\n"; //","
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for (size_t c = 0; c < newParDraw.getSize()-1; ++c)
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drawfilestr << newParDraw(c) << ",";
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drawfilestr << newParDraw(newParDraw.getSize()-1) << "\n";
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}
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urandfilestr.close();
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drawfilestr.close();
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return (double) accepted/(nMHruns-startDraw+1);
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};
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};
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#endif // !defined(A6BBC5E0_598E_4863_B7FF_E87320056B80__INCLUDED_)
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