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function oo_ = prior_analysis(type,arg1,arg2,arg3,options_,M_,oo_,estim_params_)
% Copyright (C) 2009-2012 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 <http://www.gnu.org/licenses/>.
info = check_prior_analysis_data(type,M_);
SampleSize = options_.prior_mc;
switch info
case {0,1,2}
MaxMegaBytes = options_.MaximumNumberOfMegaBytes;
drsize = size_of_the_reduced_form_model(oo_.dr);
if drsize*SampleSize>MaxMegaBytes
drsave=0;
else
drsave=1;
end
load([M_.dname '/prior/definition.mat']);
prior_sampler(drsave,M_,bayestopt_,options_,oo_,estim_params_);
clear('bayestopt_');
oo_ = job(type,SampleSize,arg1,arg2,arg3,options_,M_,oo_);
case {4,5}
oo_ = job(type,SampleSize,arg1,arg2,arg3,options_,M_,oo_);
case 6
[ivar,vartan] = get_variables_list(options_,M_);
nvar = length(ivar);
oo_ = job(type,SampleSize,arg1,arg2,arg3,options_,M_,oo_,nvar,vartan);
otherwise
error(['prior_analysis:: Check_prior_analysis_data gave a meaningless output!'])
end
function oo_ = job(type,SampleSize,arg1,arg2,arg3,options_,M_,oo_,nvar,vartan)
narg1 = 8;
narg2 = 10;
if ~(nargin==narg1 || nargin==narg2)
error('prior_analysis:: Call to function job is buggy!')
end
switch type
case 'variance'
if nargin==narg1
[nvar,vartan,NumberOfFiles] = ...
dsge_simulated_theoretical_covariance(SampleSize,M_,options_,oo_,'prior');
end
oo_ = covariance_mc_analysis(SampleSize,'prior',M_.dname,M_.fname,...
vartan,nvar,arg1,arg2,options_.mh_conf_sig,oo_);
case 'decomposition'
if nargin==narg1
[nvar,vartan,NumberOfFiles] = ...
dsge_simulated_theoretical_variance_decomposition(SampleSize,M_,options_,oo_,'prior');
end
oo_ = variance_decomposition_mc_analysis(SampleSize,'prior',M_.dname,M_.fname,...
M_.exo_names,arg2,vartan,arg1,options_.mh_conf_sig,oo_);
case 'correlation'
if nargin==narg1
[nvar,vartan,NumberOfFiles] = ...
dsge_simulated_theoretical_correlation(SampleSize,arg3,M_,options_,oo_,'prior');
end
oo_ = correlation_mc_analysis(SampleSize,'prior',M_.dname,M_.fname,...
vartan,nvar,arg1,arg2,arg3,options_.mh_conf_sig,oo_,M_,options_);
case 'conditional decomposition'
if nargin==narg1
[nvar,vartan,NumberOfFiles] = ...
dsge_simulated_theoretical_conditional_variance_decomposition(SampleSize,arg3,M_,options_,oo_,'prior');
end
oo_ = conditional_variance_decomposition_mc_analysis(SampleSize,'prior',M_.dname,M_.fname,...
arg3,M_.exo_names,arg2,vartan,arg1,options_.mh_conf_sig,oo_);
otherwise
disp('Not yet implemented')
end
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