108 lines
4.9 KiB
Matlab
108 lines
4.9 KiB
Matlab
function oo_=execute_prior_posterior_function(posterior_function_name,M_,options_,oo_,estim_params_,bayestopt_,dataset_,dataset_info,type)
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%[oo_] = execute_prior_posterior_function(posterior_function_name,M_,options_,oo_,estim_params_,bayestopt_,dataset_,dataset_info,type)
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% This function executes a given function on draws of the posterior or prior distribution
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%
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% INPUTS
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% functionhandle Handle to the function to be executed
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% M_ [structure] Matlab/Octave structure describing the Model (initialized by dynare, see @ref{M_}).
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% options_ [structure] Matlab/Octave structure describing the options (initialized by dynare, see @ref{options_}).
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% oo_ [structure] Matlab/Octave structure gathering the results (initialized by dynare, see @ref{oo_}).
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% estim_params_[structure] Matlab/Octave structure describing the estimated_parameters (initialized by dynare, see @ref{estim_params_}).
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% bayestopt_ [structure] Matlab/Octave structure describing the parameter options (initialized by dynare, see @ref{bayestopt_}).
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% dataset_ [structure] Matlab/Octave structure storing the dataset
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% dataset_info [structure] Matlab/Octave structure storing the information about the dataset
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% type [string] 'prior' or 'posterior'
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%
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%
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% OUTPUTS
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% oo_ [structure] Matlab/Octave structure gathering the results (initialized by dynare, see @ref{oo_}).
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% Copyright © 2013-2023 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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[~,basename,extension] = fileparts(posterior_function_name);
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if isempty(extension)
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extension = '.m';
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end
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fullname = [basename extension];
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if ~strcmp(extension,'.m') %if not m-file
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error('The Posterior Function is not an m-file.')
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elseif ~exist(fullname,'file') %if m-file, but does not exist
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error(['The Posterior Function ', fullname ,' was not found. Check the spelling.']);
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end
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%Create function handle
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functionhandle=str2func(posterior_function_name);
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n_draws=options_.sampling_draws;
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if strcmpi(type,'posterior')
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% Get informations about the _posterior_draws files.
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% discard first mh_drop percent of the draws:
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CutSample(M_, options_, 'prior_posterior_function');
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% initialize metropolis draws
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options_.sub_draws = n_draws; % set draws for sampling; changed value is not returned to base workspace
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[error_flag, ~, options_] = metropolis_draw(1, options_, estim_params_, M_);
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if error_flag
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error('EXECUTE_POSTERIOR_FUNCTION: The draws could not be initialized')
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end
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n_draws = options_.sub_draws;
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elseif strcmpi(type,'prior')
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% Get informations about the prior distribution.
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if isempty(bayestopt_)
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if ~isempty(estim_params_) && ~(isfield(estim_params_,'nvx') && (size(estim_params_.var_exo,1)+size(estim_params_.var_endo,1)+size(estim_params_.corrx,1)+size(estim_params_.corrn,1)+size(estim_params_.param_vals,1))==0)
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[~,estim_params_,bayestopt_,~,~,M_] = set_prior(estim_params_,M_,options_);
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else
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error('The prior distributions are not properly set up.')
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end
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end
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if exist([M_.fname '_prior_restrictions.m'])
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warning('prior_function currently does not support endogenous prior restrictions. They will be ignored. Consider using a posterior_function with nobs=1.')
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end
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Prior = dprior(bayestopt_, options_.prior_trunc);
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else
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error('EXECUTE_POSTERIOR_FUNCTION: Unknown type!')
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end
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if strcmpi(type, 'prior')
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parameter_mat = Prior.draws(n_draws);
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else
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parameter_mat = NaN(length(bayestopt_.p6), n_draws);
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for i = 1:n_draws
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parameter_mat(:,i) = GetOneDraw(type, M_, estim_params_, oo_, options_, bayestopt_);
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end
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end
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% Get output size
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try
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junk = functionhandle(parameter_mat(:,1), M_, options_, oo_, estim_params_, bayestopt_, dataset_, dataset_info);
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catch err
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fprintf('\nEXECUTE_POSTERIOR_FUNCTION: Execution of prior/posterior function led to an error. Execution cancelled.\n')
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rethrow(err)
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end
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% Initialize cell with number of columns
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results_cell = cell(n_draws, columns(junk));
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% Evaluate function on each draw
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for i = 1:n_draws
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M_ = set_all_parameters(parameter_mat(:,i), estim_params_, M_);
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[results_cell(i,:)] = functionhandle(parameter_mat(:,i), M_, options_, oo_, estim_params_, bayestopt_, dataset_, dataset_info);
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end
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% Save results under oo_
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oo_.(sprintf('%s_function_results', type)) = results_cell;
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