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