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function [oo_,M_,options_,bayestopt_,Smoothed_variables_declaration_order_deviation_form,initial_date]=evaluate_smoother(parameters,var_list,M_,oo_,options_,bayestopt_,estim_params_)
% Evaluate the smoother at parameters.
%
% INPUTS
% o parameters a string ('posterior mode','posterior mean','posterior median','prior mode','prior mean','mle_mode','calibration') or a vector of values for
% the (estimated) parameters of the model.
% o var_list subset of endogenous variables
% o M_ [structure] Definition of the model
% o oo_ [structure] Storage of results
% o options_ [structure] Options
% o bayestopt_ [structure] describing the priors
% o estim_params_ [structure] characterizing parameters to be estimated
%
% OUTPUTS
% o oo [structure] results:
% - SmoothedVariables
% - SmoothedShocks
% - FilteredVariablesShockDecomposition
% - UpdatedVariables
% - FilteredVariables
% - SmoothedMeasurementErrors
% - FilteredVariablesKStepAhead
% - FilteredVariablesKStepAheadVariances
% o M_ [structure] Definition of the model
% o options_ [structure] Options; returns options_.first_obs
% o bayestopt_ [structure] describing the priors; returns fields like bayestopt_.smoother_var_list from the smoother
% o Smoothed_variables_declaration_order_deviation_form
% Smoothed variables from the Kalman smoother in
% order of declaration of variables (M_.endo_names)
% in deviations from their respective mean, i.e.
% without trend and constant part (used for shock_decomposition)
% o initial_date [dseries] initial period, used for shock_decomposition
%
% SPECIAL REQUIREMENTS
% None
%
% REMARKS
% [1] This function use persistent variables for the dataset and the description of the missing observations. Consequently, if this function
% is called more than once (by changing the value of parameters) the sample *must not* change.
% Copyright (C) 2010-2020 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/>.
% store qz_criterium
qz_criterium_old=options_.qz_criterium;
if ischar(parameters) && strcmp(parameters,'calibration')
options_.smoother=1;
end
[dataset_,dataset_info, ~, ~, M_, options_, oo_, estim_params_,bayestopt_] = dynare_estimation_init(var_list, M_.fname, [], M_, options_, oo_, estim_params_, bayestopt_);
initial_date=dataset_.firstdate;
% set the qz_criterium
options_=select_qz_criterium_value(options_);
if nargin==0
parameters = 'posterior_mode';
end
if ischar(parameters)
switch parameters
case 'posterior_mode'
parameters = get_posterior_parameters('mode',M_,estim_params_,oo_,options_);
case 'posterior_mean'
parameters = get_posterior_parameters('mean',M_,estim_params_,oo_,options_);
case 'posterior_median'
parameters = get_posterior_parameters('median',M_,estim_params_,oo_,options_);
case 'mle_mode'
parameters = get_posterior_parameters('mode',M_,estim_params_,oo_,options_,'mle_');
case 'prior_mode'
parameters = bayestopt_.p5(:);
case 'prior_mean'
parameters = bayestopt_.p1;
case 'calibration'
if isempty(oo_.dr)
error('You must run ''stoch_simul'' first.');
end
parameters = [];
otherwise
disp('evaluate_smoother:: If the input argument is a string, then it has to be equal to:')
disp(' ''posterior_mode'', ')
disp(' ''posterior_mean'', ')
disp(' ''posterior_median'', ')
disp(' ''prior_mode'' or')
disp(' ''prior_mean''.')
disp(' ''calibration''.')
error
end
end
if options_.occbin.smoother.status
if options_.occbin.smoother.inversion_filter
[~, ~, ~, ~, ~, ~, ~, ~, ~, ~, oo_, atT, innov] = occbin.IVF_posterior(parameters,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,prior_bounds(bayestopt_,options_.prior_trunc),oo_);
updated_variables = atT*nan;
measurement_error=[];
ys = oo_.dr.ys;
trend_coeff = zeros(length(options_.varobs_id),1);
bayestopt_.mf = bayestopt_.smoother_var_list(bayestopt_.smoother_mf);
else
[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp,Trend,state_uncertainty,M_,oo_,bayestopt_] = ...
occbin.DSGE_smoother(parameters,dataset_.nobs,transpose(dataset_.data),dataset_info.missing.aindex,dataset_info.missing.state,M_,oo_,options_,bayestopt_,estim_params_,dataset_,dataset_info);
end
else
[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp,Trend,state_uncertainty,M_,oo_,bayestopt_] = ...
DsgeSmoother(parameters,dataset_.nobs,transpose(dataset_.data),dataset_info.missing.aindex,dataset_info.missing.state,M_,oo_,options_,bayestopt_,estim_params_);
end
if ~(options_.occbin.smoother.status && options_.occbin.smoother.inversion_filter)
if ~options_.occbin.smoother.status || (options_.occbin.smoother.status && oo_.occbin.smoother.error_flag==0)
[oo_]=store_smoother_results(M_,oo_,options_,bayestopt_,dataset_,dataset_info,atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,P,PK,decomp,Trend,state_uncertainty);
end
else
[oo_]=store_smoother_results(M_,oo_,options_,bayestopt_,dataset_,dataset_info,atT,innov,measurement_error,updated_variables,ys,trend_coeff);
end
if nargout>4
Smoothed_variables_declaration_order_deviation_form=atT(oo_.dr.inv_order_var(bayestopt_.smoother_var_list),:);
end
%reset qz_criterium
options_.qz_criterium=qz_criterium_old;
oo_.gui.ran_calib_smoother = true;
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