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dynare/matlab/PosteriorIRF_core1.m

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