114 lines
4.7 KiB
Matlab
114 lines
4.7 KiB
Matlab
function [ ix2, temperedlogpost, loglik, bayestopt_] = ...
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SMC_samplers_initialization(TargetFun, xparam1, mh_bounds, dataset_, dataset_info, options_, M_, estim_params_, bayestopt_, oo_, NumberOfParticles)
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% function [ ix2, ilogpo2, ModelName, MetropolisFolder, FirstBlock, FirstLine, npar, NumberOfParticles, bayestopt_] = ...
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% SMC_samplers_initialization(TargetFun, xparam1, mh_bounds,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,oo_,NumberOfParticles)
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% Draw in prior distribution to initialize samplers.
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%
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% INPUTS
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% o TargetFun [char] string specifying the name of the objective
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% function (tempered posterior kernel and likelihood).
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% o xparam1 [double] (p*1) vector of parameters to be estimated (initial values).
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% o mh_bounds [double] (p*2) matrix defining lower and upper bounds for the parameters.
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% o dataset_ data structure
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% o dataset_info dataset info structure
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% o options_ options structure
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% o M_ model structure
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% o estim_params_ estimated parameters structure
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% o bayestopt_ estimation options structure
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% o oo_ outputs structure
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%
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% OUTPUTS
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% o ix2 [double] (NumberOfParticles*npar) vector of starting points for different chains
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% o ilogpo2 [double] (NumberOfParticles*1) vector of initial posterior values for different chains
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% o iloglik2 [double] (NumberOfParticles*1) vector of initial likelihood values for different chains
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% o ModelName [string] name of the mod-file
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% o MetropolisFolder [string] path to the Metropolis subfolder
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% o bayestopt_ [structure] estimation options structure
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%
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% SPECIAL REQUIREMENTS
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% None.
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% Copyright © 2006-2022 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 <https://www.gnu.org/licenses/>.
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%Initialize outputs
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ix2 = [];
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ilogpo2 = [];
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iloglik2 = [];
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ModelName = [];
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MetropolisFolder = [];
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ModelName = M_.fname;
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if ~isempty(M_.bvar)
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ModelName = [ModelName '_bvar'];
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end
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MetropolisFolder = CheckPath('dsmh',M_.dname);
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BaseName = [MetropolisFolder filesep ModelName];
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npar = length(xparam1);
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% Here we start a new DS Metropolis-Hastings, previous draws are discarded.
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disp('Estimation:: Initialization...')
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% Delete old dsmh files if any...
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files = dir([BaseName '_dsmh*_blck*.mat']);
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%if length(files)
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% delete([BaseName '_dsmh*_blck*.mat']);
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% disp('Estimation::smc: Old dsmh-files successfully erased!')
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%end
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% Delete old log file.
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file = dir([ MetropolisFolder '/dsmh.log']);
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%if length(file)
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% delete([ MetropolisFolder '/dsmh.log']);
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% disp('Estimation::dsmh: Old dsmh.log file successfully erased!')
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% disp('Estimation::dsmh: Creation of a new dsmh.log file.')
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%end
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fidlog = fopen([MetropolisFolder '/dsmh.log'],'w');
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fprintf(fidlog,'%% DSMH log file (Dynare).\n');
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fprintf(fidlog,['%% ' datestr(now,0) '.\n']);
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fprintf(fidlog,' \n\n');
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fprintf(fidlog,'%% Session 1.\n');
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fprintf(fidlog,' \n');
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prior_draw(bayestopt_,options_.prior_trunc);
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% Find initial values for the NumberOfParticles chains...
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options_=set_dynare_seed_local_options(options_,'default');
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fprintf(fidlog,[' Initial values of the parameters:\n']);
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disp('Estimation::dsmh: Searching for initial values...');
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ix2 = zeros(npar,NumberOfParticles);
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temperedlogpost = zeros(NumberOfParticles,1);
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loglik = zeros(NumberOfParticles,1);
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%stderr = sqrt(bsxfun(@power,mh_bounds.ub-mh_bounds.lb,2)/12)/10;
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for j=1:NumberOfParticles
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validate = 0;
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while validate == 0
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candidate = prior_draw()';
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% candidate = xparam1(:) + 0.001*randn(npar,1);%bsxfun(@times,stderr,randn(npar,1)) ;
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if all(candidate(:) >= mh_bounds.lb) && all(candidate(:) <= mh_bounds.ub)
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ix2(:,j) = candidate ;
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[temperedlogpost(j),loglik(j)] = tempered_likelihood(TargetFun,candidate,0.0,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,mh_bounds,oo_);
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if isfinite(loglik(j)) % if returned log-density is Inf or Nan (penalized value)
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validate = 1;
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end
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end
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end
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end
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fprintf(fidlog,' \n');
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disp('Estimation:: Initial values found!')
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skipline()
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