340 lines
12 KiB
Matlab
340 lines
12 KiB
Matlab
function myoutput=prior_posterior_statistics_core(myinputs,fpar,B,whoiam, ThisMatlab)
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% PARALLEL CONTEXT
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% Core functionality for prior_posterior.m function, which can be parallelized.
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% See also the comment in random_walk_metropolis_hastings_core.m funtion.
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%
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% INPUTS
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% See See the comment in random_walk_metropolis_hastings_core.m funtion.
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%
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% OUTPUTS
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% o myoutput [struc]
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% Contained OutputFileName_smooth;
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% _update;
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% _inno;
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% _error;
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% _filter_step_ahead;
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% _param;
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% _forc_mean;
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% _forc_point
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%
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% ALGORITHM
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% Portion of prior_posterior.m function.
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% This file is part of Dynare.
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%
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% SPECIAL REQUIREMENTS.
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% None.
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% Copyright (C) 2005-2013 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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global options_ oo_ M_ bayestopt_ estim_params_
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if nargin<4,
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whoiam=0;
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end
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% Reshape 'myinputs' for local computation.
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% In order to avoid confusion in the name space, the instruction struct2local(myinputs) is replaced by:
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type=myinputs.type;
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run_smoother=myinputs.run_smoother;
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gend=myinputs.gend;
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Y=myinputs.Y;
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data_index=myinputs.data_index;
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missing_value=myinputs.missing_value;
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varobs=myinputs.varobs;
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irun=myinputs.irun;
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endo_nbr=myinputs.endo_nbr;
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nvn=myinputs.nvn;
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naK=myinputs.naK;
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horizon=myinputs.horizon;
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iendo=myinputs.iendo;
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if horizon
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i_last_obs=myinputs.i_last_obs;
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IdObs=myinputs.IdObs;
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MAX_nforc1=myinputs.MAX_nforc1;
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MAX_nforc2=myinputs.MAX_nforc2;
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end
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if naK
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MAX_naK=myinputs.MAX_naK;
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end
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exo_nbr=myinputs.exo_nbr;
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maxlag=myinputs.maxlag;
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MAX_nsmoo=myinputs.MAX_nsmoo;
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MAX_ninno=myinputs.MAX_ninno;
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MAX_nerro = myinputs.MAX_nerro;
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MAX_nruns=myinputs.MAX_nruns;
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MAX_momentsno = myinputs.MAX_momentsno;
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ifil=myinputs.ifil;
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if ~strcmpi(type,'prior'),
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x=myinputs.x;
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if strcmpi(type,'posterior'),
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logpost=myinputs.logpost;
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end
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end
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if whoiam
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Parallel=myinputs.Parallel;
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end
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% DirectoryName = myinputs.DirectoryName;
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if strcmpi(type,'posterior')
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DirectoryName = CheckPath('metropolis',M_.dname);
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elseif strcmpi(type,'gsa')
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if options_.opt_gsa.pprior
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DirectoryName = CheckPath(['gsa',filesep,'prior'],M_.dname);
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else
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DirectoryName = CheckPath(['gsa',filesep,'mc'],M_.dname);
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end
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elseif strcmpi(type,'prior')
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DirectoryName = CheckPath('prior',M_.dname);
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end
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RemoteFlag = 0;
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if whoiam
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if Parallel(ThisMatlab).Local==0,
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RemoteFlag =1;
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end
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ifil=ifil(:,whoiam);
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prct0={0,whoiam,Parallel(ThisMatlab)};
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else
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prct0=0;
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end
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h = dyn_waitbar(prct0,['Taking ',type,' subdraws...']);
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if RemoteFlag==1,
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OutputFileName_smooth = {};
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OutputFileName_update = {};
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OutputFileName_inno = {};
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OutputFileName_error = {};
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OutputFileName_filter_step_ahead = {};
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OutputFileName_param = {};
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OutputFileName_forc_mean = {};
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OutputFileName_forc_point = {};
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% OutputFileName_moments = {};
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end
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%initialize arrays
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if run_smoother
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stock_smooth=NaN(endo_nbr,gend,MAX_nsmoo);
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stock_update=NaN(endo_nbr,gend,MAX_nsmoo);
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stock_innov=NaN(M_.exo_nbr,gend,MAX_ninno);
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if horizon
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stock_forcst_mean= NaN(endo_nbr,horizon+maxlag,MAX_nforc1);
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stock_forcst_point = NaN(endo_nbr,horizon+maxlag,MAX_nforc2);
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end
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end
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if nvn
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stock_error = NaN(size(varobs,1),gend,MAX_nerro);
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end
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if naK
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stock_filter_step_ahead =NaN(length(options_.filter_step_ahead),endo_nbr,gend+max(options_.filter_step_ahead),MAX_naK);
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end
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stock_param = NaN(MAX_nruns,size(myinputs.x,2));
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stock_logpo = NaN(MAX_nruns,1);
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stock_ys = NaN(MAX_nruns,endo_nbr);
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for b=fpar:B
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% [deep, logpo] = GetOneDraw(type);
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% set_all_parameters(deep);
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% dr = resol(oo_.steady_state,0);
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if strcmpi(type,'prior')
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[deep, logpo] = GetOneDraw(type);
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else
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deep = x(b,:);
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if strcmpi(type,'posterior')
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logpo = logpost(b);
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else
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logpo = evaluate_posterior_kernel(deep');
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end
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end
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M_ = set_all_parameters(deep,estim_params_,M_);
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if run_smoother
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[dr,info,M_,options_,oo_] = resol(0,M_,options_,oo_);
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[alphahat,etahat,epsilonhat,alphatilde,SteadyState,trend_coeff,aK] = ...
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DsgeSmoother(deep,gend,Y,data_index,missing_value);
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if options_.loglinear
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stock_smooth(dr.order_var,:,irun(1)) = alphahat(1:endo_nbr,:)+ ...
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repmat(log(SteadyState(dr.order_var)),1,gend);
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stock_update(dr.order_var,:,irun(1)) = alphatilde(1:endo_nbr,:)+ ...
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repmat(log(SteadyState(dr.order_var)),1,gend);
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else
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stock_smooth(dr.order_var,:,irun(1)) = alphahat(1:endo_nbr,:)+ ...
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repmat(SteadyState(dr.order_var),1,gend);
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stock_update(dr.order_var,:,irun(1)) = alphatilde(1:endo_nbr,:)+ ...
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repmat(SteadyState(dr.order_var),1,gend);
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end
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stock_innov(:,:,irun(2)) = etahat;
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if nvn
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stock_error(:,:,irun(3)) = epsilonhat;
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end
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if naK
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stock_filter_step_ahead(:,dr.order_var,:,irun(4)) = aK(options_.filter_step_ahead,1:endo_nbr,:);
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end
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if horizon
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yyyy = alphahat(iendo,i_last_obs);
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yf = forcst2a(yyyy,dr,zeros(horizon,exo_nbr));
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if options_.prefilter == 1
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yf(:,IdObs) = yf(:,IdObs)+repmat(bayestopt_.mean_varobs', ...
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horizon+maxlag,1);
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end
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yf(:,IdObs) = yf(:,IdObs)+(gend+[1-maxlag:horizon]')*trend_coeff';
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if options_.loglinear == 1
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yf = yf+repmat(log(SteadyState'),horizon+maxlag,1);
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else
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yf = yf+repmat(SteadyState',horizon+maxlag,1);
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end
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yf1 = forcst2(yyyy,horizon,dr,1);
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if options_.prefilter == 1
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yf1(:,IdObs,:) = yf1(:,IdObs,:)+ ...
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repmat(bayestopt_.mean_varobs',[horizon+maxlag,1,1]);
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end
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yf1(:,IdObs,:) = yf1(:,IdObs,:)+repmat((gend+[1-maxlag:horizon]')* ...
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trend_coeff',[1,1,1]);
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if options_.loglinear == 1
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yf1 = yf1 + repmat(log(SteadyState'),[horizon+maxlag,1,1]);
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else
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yf1 = yf1 + repmat(SteadyState',[horizon+maxlag,1,1]);
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end
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stock_forcst_mean(:,:,irun(6)) = yf';
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stock_forcst_point(:,:,irun(7)) = yf1';
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end
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else
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[T,R,SteadyState,info,M_,options_,oo_] = dynare_resolve(M_,options_,oo_);
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end
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stock_param(irun(5),:) = deep;
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stock_logpo(irun(5),1) = logpo;
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stock_ys(irun(5),:) = SteadyState';
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irun = irun + ones(7,1);
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if run_smoother && (irun(1) > MAX_nsmoo || b == B),
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stock = stock_smooth(:,:,1:irun(1)-1);
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ifil(1) = ifil(1) + 1;
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save([DirectoryName '/' M_.fname '_smooth' int2str(ifil(1)) '.mat'],'stock');
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stock = stock_update(:,:,1:irun(1)-1);
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save([DirectoryName '/' M_.fname '_update' int2str(ifil(1)) '.mat'],'stock');
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if RemoteFlag==1,
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OutputFileName_smooth = [OutputFileName_smooth; {[DirectoryName filesep], [M_.fname '_smooth' int2str(ifil(1)) '.mat']}];
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OutputFileName_update = [OutputFileName_update; {[DirectoryName filesep], [M_.fname '_update' int2str(ifil(1)) '.mat']}];
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end
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irun(1) = 1;
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end
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if run_smoother && (irun(2) > MAX_ninno || b == B)
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stock = stock_innov(:,:,1:irun(2)-1);
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ifil(2) = ifil(2) + 1;
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save([DirectoryName '/' M_.fname '_inno' int2str(ifil(2)) '.mat'],'stock');
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if RemoteFlag==1,
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OutputFileName_inno = [OutputFileName_inno; {[DirectoryName filesep], [M_.fname '_inno' int2str(ifil(2)) '.mat']}];
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end
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irun(2) = 1;
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end
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if run_smoother && nvn && (irun(3) > MAX_nerro || b == B)
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stock = stock_error(:,:,1:irun(3)-1);
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ifil(3) = ifil(3) + 1;
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save([DirectoryName '/' M_.fname '_error' int2str(ifil(3)) '.mat'],'stock');
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if RemoteFlag==1,
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OutputFileName_error = [OutputFileName_error; {[DirectoryName filesep], [M_.fname '_error' int2str(ifil(3)) '.mat']}];
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end
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irun(3) = 1;
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end
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if run_smoother && naK && (irun(4) > MAX_naK || b == B)
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stock = stock_filter_step_ahead(:,:,:,1:irun(4)-1);
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ifil(4) = ifil(4) + 1;
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save([DirectoryName '/' M_.fname '_filter_step_ahead' int2str(ifil(4)) '.mat'],'stock');
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if RemoteFlag==1,
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OutputFileName_filter_step_ahead = [OutputFileName_filter_step_ahead; {[DirectoryName filesep], [M_.fname '_filter_step_ahead' int2str(ifil(4)) '.mat']}];
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end
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irun(4) = 1;
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end
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if irun(5) > MAX_nruns || b == B
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stock = stock_param(1:irun(5)-1,:);
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ifil(5) = ifil(5) + 1;
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save([DirectoryName '/' M_.fname '_param' int2str(ifil(5)) '.mat'],'stock','stock_logpo','stock_ys');
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if RemoteFlag==1,
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OutputFileName_param = [OutputFileName_param; {[DirectoryName filesep], [M_.fname '_param' int2str(ifil(5)) '.mat']}];
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end
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irun(5) = 1;
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end
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if run_smoother && horizon && (irun(6) > MAX_nforc1 || b == B)
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stock = stock_forcst_mean(:,:,1:irun(6)-1);
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ifil(6) = ifil(6) + 1;
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save([DirectoryName '/' M_.fname '_forc_mean' int2str(ifil(6)) '.mat'],'stock');
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if RemoteFlag==1,
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OutputFileName_forc_mean = [OutputFileName_forc_mean; {[DirectoryName filesep], [M_.fname '_forc_mean' int2str(ifil(6)) '.mat']}];
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end
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irun(6) = 1;
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end
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if run_smoother && horizon && (irun(7) > MAX_nforc2 || b == B)
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stock = stock_forcst_point(:,:,1:irun(7)-1);
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ifil(7) = ifil(7) + 1;
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save([DirectoryName '/' M_.fname '_forc_point' int2str(ifil(7)) '.mat'],'stock');
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if RemoteFlag==1,
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OutputFileName_forc_point = [OutputFileName_forc_point; {[DirectoryName filesep], [M_.fname '_forc_point' int2str(ifil(7)) '.mat']}];
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end
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irun(7) = 1;
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end
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% if moments_varendo && (irun(8) > MAX_momentsno || b == B)
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% stock = stock_moments(1:irun(8)-1);
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% ifil(8) = ifil(8) + 1;
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% save([DirectoryName '/' M_.fname '_moments' int2str(ifil(8)) '.mat'],'stock');
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% if RemoteFlag==1,
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% OutputFileName_moments = [OutputFileName_moments; {[DirectoryName filesep], [M_.fname '_moments' int2str(ifil(8)) '.mat']}];
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% end
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% irun(8) = 1;
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% end
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% DirectoryName=TempPath;
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dyn_waitbar((b-fpar+1)/(B-fpar+1),h);
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end
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myoutput.ifil=ifil;
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if RemoteFlag==1,
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myoutput.OutputFileName = [OutputFileName_smooth;
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OutputFileName_update;
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OutputFileName_inno;
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OutputFileName_error;
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OutputFileName_filter_step_ahead;
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OutputFileName_param;
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OutputFileName_forc_mean;
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OutputFileName_forc_point];
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% OutputFileName_moments];
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end
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dyn_waitbar_close(h);
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