301 lines
11 KiB
Matlab
301 lines
11 KiB
Matlab
function myoutput=PosteriorIRF_core1(myinputs,fpar,B,whoiam, ThisMatlab)
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% Generates and stores Posterior IRFs
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% PARALLEL CONTEXT
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% This function perfoms in parallel execution a portion of the PosteriorIRF.m code.
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% This is a special kind of parallel function. Unlike of other parallel functions,
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% that running in parallel a 'for' cycle, this function run in parallel a
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% 'while' loop! The parallelization of 'while' loop (when possible) is a more
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% sophisticated procedure.
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%
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% See also the comment in posterior_sampler_core.m funtion.
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%
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% INPUTS
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% See the comment in posterior_sampler_core.m funtion.
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%
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% OUTPUTS
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% o myoutput [struc]
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% Contained:
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% OutputFileName_dsge, OutputFileName_param and OutputFileName_bvardsge.
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%
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% ALGORITHM
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% Portion of PosteriorIRF.m function. Specifically the 'while' cycle.
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%
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% SPECIAL REQUIREMENTS.
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% None.
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%
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% Copyright (C) 2006-2019 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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global options_ estim_params_ oo_ M_ bayestopt_ dataset_ dataset_info
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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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IRUN = myinputs.IRUN;
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irun =myinputs.irun;
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irun2=myinputs.irun2;
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npar=myinputs.npar;
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type=myinputs.type;
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if ~strcmpi(type,'prior')
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x=myinputs.x;
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end
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nvar=myinputs.nvar;
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IndxVariables=myinputs.IndxVariables;
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MAX_nirfs_dsgevar=myinputs.MAX_nirfs_dsgevar;
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MAX_nirfs_dsge=myinputs.MAX_nirfs_dsge;
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MAX_nruns=myinputs.MAX_nruns;
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NumberOfIRFfiles_dsge=myinputs.NumberOfIRFfiles_dsge;
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NumberOfIRFfiles_dsgevar=myinputs.NumberOfIRFfiles_dsgevar;
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ifil2=myinputs.ifil2;
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if options_.dsge_var
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nvobs=myinputs.nvobs;
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NumberOfParametersPerEquation = myinputs.NumberOfParametersPerEquation;
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NumberOfLagsTimesNvobs = myinputs.NumberOfLagsTimesNvobs;
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Companion_matrix = myinputs.Companion_matrix;
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stock_irf_bvardsge = zeros(options_.irf,nvobs,M_.exo_nbr,MAX_nirfs_dsgevar);
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bounds = prior_bounds(bayestopt_,options_.prior_trunc);
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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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% MhDirectoryName = myinputs.MhDirectoryName;
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if strcmpi(type,'posterior')
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MhDirectoryName = 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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MhDirectoryName = CheckPath(['gsa' filesep 'prior'],M_.dname);
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else
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MhDirectoryName = CheckPath(['gsa' filesep 'mc'],M_.dname);
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end
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else
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MhDirectoryName = 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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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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if strcmpi(type,'posterior')
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h = dyn_waitbar(prct0,'Bayesian (posterior) IRFs...');
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elseif strcmpi(type,'gsa')
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h = dyn_waitbar(prct0,'GSA (prior) IRFs...');
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else
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h = dyn_waitbar(prct0,'Bayesian (prior) IRFs...');
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end
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OutputFileName_bvardsge = {};
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OutputFileName_dsge = {};
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OutputFileName_param = {};
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fpar = fpar-1;
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fpar0=fpar;
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nosaddle=0;
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if whoiam
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ifil2=ifil2(whoiam);
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NumberOfIRFfiles_dsge=NumberOfIRFfiles_dsge(whoiam);
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NumberOfIRFfiles_dsgevar=NumberOfIRFfiles_dsgevar(whoiam);
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end
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% Parallel 'while' very good!!!
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stock_param=zeros(MAX_nruns,npar);
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stock_irf_dsge=zeros(options_.irf,nvar,M_.exo_nbr,MAX_nirfs_dsge);
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while fpar<B
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fpar = fpar + 1;
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irun = irun+1;
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irun2 = irun2+1;
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if strcmpi(type,'prior')
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deep = GetOneDraw(type,M_,estim_params_,oo_,options_,bayestopt_);
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else
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deep = x(fpar,:);
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end
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stock_param(irun2,:) = deep;
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set_parameters(deep);
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[dr,info,M_,oo_] =compute_decision_rules(M_,options_,oo_);
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oo_.dr = dr;
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if info(1)
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nosaddle = nosaddle + 1;
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fpar = fpar - 1;
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irun = irun-1;
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irun2 = irun2-1;
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if info(1) == 1
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errordef = 'Static variables are not uniquely defined';
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elseif info(1) == 2
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errordef = 'Dll problem';
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elseif info(1) == 3
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errordef = 'No stable trajectory';
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elseif info(1) == 4
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errordef = 'Indeterminacy';
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elseif info(1) == 5
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errordef = 'Rank condition is not satisfied';
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else
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errordef = get_error_message(info, options_);
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end
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if strcmpi(type,'prior')
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disp(['PosteriorIRF :: Dynare is unable to solve the model (' errordef ')'])
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continue
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else
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error(['PosteriorIRF :: Dynare is unable to solve the model (' errordef ') with sample ' type])
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end
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end
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SS(M_.exo_names_orig_ord,M_.exo_names_orig_ord) = M_.Sigma_e+1e-14*eye(M_.exo_nbr);
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SS = transpose(chol(SS));
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irf_shocks_indx = getIrfShocksIndx();
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for i=irf_shocks_indx
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if SS(i,i) > 1e-13
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if options_.order>1 && options_.relative_irf % normalize shock to 0.01 before IRF generation for GIRFs; multiply with 100 later
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y=irf(M_,options_,dr,SS(M_.exo_names_orig_ord,i)./SS(i,i)/100, options_.irf, options_.drop,options_.replic,options_.order);
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else
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y=irf(M_,options_,dr,SS(M_.exo_names_orig_ord,i), options_.irf, options_.drop,options_.replic,options_.order);
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end
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if options_.relative_irf && options_.order==1 %multiply with 100 for backward compatibility
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y = 100*y/SS(i,i);
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end
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for j = 1:nvar
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if max(y(IndxVariables(j),:)) - min(y(IndxVariables(j),:)) > 1e-12
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stock_irf_dsge(:,j,i,irun) = transpose(y(IndxVariables(j),:));
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end
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end
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end
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end
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if MAX_nirfs_dsgevar
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IRUN = IRUN+1;
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[~,~,~,~,~,~,~,PHI,SIGMAu,iXX] = dsge_var_likelihood(deep',dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,bounds,oo_);
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dsge_prior_weight = M_.params(strmatch('dsge_prior_weight', M_.param_names));
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DSGE_PRIOR_WEIGHT = floor(dataset_.nobs*(1+dsge_prior_weight));
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SIGMA_inv_upper_chol = chol(inv(SIGMAu*dataset_.nobs*(dsge_prior_weight+1)));
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explosive_var = 1;
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while explosive_var
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% draw from the marginal posterior of SIGMA
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SIGMAu_draw = rand_inverse_wishart(dataset_.vobs, DSGE_PRIOR_WEIGHT-NumberOfParametersPerEquation, ...
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SIGMA_inv_upper_chol);
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% draw from the conditional posterior of PHI
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PHI_draw = rand_matrix_normal(NumberOfParametersPerEquation,dataset_.vobs, PHI, ...
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chol(SIGMAu_draw)', chol(iXX)');
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Companion_matrix(1:dataset_.vobs,:) = transpose(PHI_draw(1:NumberOfLagsTimesNvobs,:));
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% Check for stationarity
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explosive_var = any(abs(eig(Companion_matrix))>1.000000001);
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end
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% Get the mean
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mu = zeros(1,dataset_.vobs);
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% Get rotation
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if dsge_prior_weight > 0
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Atheta(oo_.dr.order_var,M_.exo_names_orig_ord) = oo_.dr.ghu*sqrt(M_.Sigma_e);
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A0 = Atheta(bayestopt_.mfys,:);
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OMEGAstar = qr2(A0');
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end
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SIGMAu_chol = chol(SIGMAu_draw)';
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SIGMAtrOMEGA = SIGMAu_chol*OMEGAstar';
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PHIpower = eye(NumberOfLagsTimesNvobs);
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irfs = zeros (options_.irf,dataset_.vobs*M_.exo_nbr);
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tmp3 = PHIpower(1:dataset_.vobs,1:dataset_.vobs)*SIGMAtrOMEGA;
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irfs(1,:) = tmp3(:)';
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for t = 2:options_.irf
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PHIpower = Companion_matrix*PHIpower;
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tmp3 = PHIpower(1:dataset_.vobs,1:dataset_.vobs)*SIGMAtrOMEGA;
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irfs(t,:) = tmp3(:)'+kron(ones(1,M_.exo_nbr),mu);
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end
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tmp_dsgevar = kron(ones(options_.irf,1),mu);
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for j = 1:(dataset_.vobs*M_.exo_nbr)
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if max(irfs(:,j)) - min(irfs(:,j)) > 1e-10
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tmp_dsgevar(:,j) = (irfs(:,j));
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end
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end
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if IRUN < MAX_nirfs_dsgevar
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stock_irf_bvardsge(:,:,:,IRUN) = reshape(tmp_dsgevar,options_.irf,dataset_.vobs,M_.exo_nbr);
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else
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stock_irf_bvardsge(:,:,:,IRUN) = reshape(tmp_dsgevar,options_.irf,dataset_.vobs,M_.exo_nbr);
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save([MhDirectoryName '/' M_.fname '_irf_bvardsge' int2str(NumberOfIRFfiles_dsgevar) '.mat'], 'stock_irf_bvardsge');
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if RemoteFlag==1
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OutputFileName_bvardsge = [OutputFileName_bvardsge; {[MhDirectoryName filesep], [M_.fname '_irf_bvardsge' int2str(NumberOfIRFfiles_dsgevar) '.mat']}];
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end
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NumberOfIRFfiles_dsgevar = NumberOfIRFfiles_dsgevar+1;
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IRUN =0;
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end
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end
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if irun == MAX_nirfs_dsge || irun == B || fpar == B
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if fpar == B
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stock_irf_dsge = stock_irf_dsge(:,:,:,1:irun);
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if MAX_nirfs_dsgevar && (fpar == B || IRUN == B)
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stock_irf_bvardsge = stock_irf_bvardsge(:,:,:,1:IRUN);
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save([MhDirectoryName '/' M_.fname '_irf_bvardsge' int2str(NumberOfIRFfiles_dsgevar) '.mat'], 'stock_irf_bvardsge');
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NumberOfIRFfiles_dsgevar = NumberOfIRFfiles_dsgevar+1;
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if RemoteFlag==1
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OutputFileName_bvardsge = [OutputFileName_bvardsge; {[MhDirectoryName filesep], [M_.fname '_irf_bvardsge' int2str(NumberOfIRFfiles_dsgevar) '.mat']}];
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end
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irun = 0;
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end
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end
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save([MhDirectoryName '/' M_.fname '_irf_dsge' int2str(NumberOfIRFfiles_dsge) '.mat'],'stock_irf_dsge');
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if RemoteFlag==1
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OutputFileName_dsge = [OutputFileName_dsge; {[MhDirectoryName filesep], [M_.fname '_irf_dsge' int2str(NumberOfIRFfiles_dsge) '.mat']}];
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end
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NumberOfIRFfiles_dsge = NumberOfIRFfiles_dsge+1;
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irun = 0;
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end
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if irun2 == MAX_nruns || fpar == B
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if fpar == B
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stock_param = stock_param(1:irun2,:);
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end
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stock = stock_param;
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save([MhDirectoryName '/' M_.fname '_param_irf' int2str(ifil2) '.mat'],'stock');
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if RemoteFlag==1
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OutputFileName_param = [OutputFileName_param; {[MhDirectoryName filesep], [M_.fname '_param_irf' int2str(ifil2) '.mat']}];
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end
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ifil2 = ifil2 + 1;
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irun2 = 0;
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end
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dyn_waitbar((fpar-fpar0)/(B-fpar0),h);
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end
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dyn_waitbar_close(h);
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if whoiam==0
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if nosaddle
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disp(['PosteriorIRF :: Percentage of discarded posterior draws = ' num2str(nosaddle/(B+nosaddle))])
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end
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end
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% Copy the rusults of computation on the call machine (specifically in the
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% directory on call machine that contain the model).
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myoutput.OutputFileName = [OutputFileName_dsge;
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OutputFileName_param;
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OutputFileName_bvardsge];
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myoutput.nosaddle = nosaddle;
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