187 lines
9.2 KiB
Matlab
187 lines
9.2 KiB
Matlab
function oo_ = convert_dyn_45_to_44(M_, options_, oo_,bayestopt_)
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%function oo_ = convert_dyn_45_to_44(M_, options_, oo_,bayestopt_)
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% Converts oo_ from 4.5 to 4.4
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%
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% INPUTS
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% M_ [struct] dynare model struct
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% options_ [struct] dynare options struct
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% oo_ [struct] dynare output struct
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% bayestopt_ [struct] structure storing information about priors
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% OUTPUTS
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% oo_ [struct] dynare output struct
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright (C) 2015-2016 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 <http://www.gnu.org/licenses/>.
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%% add initial conditions to Bayesian forecasts
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if isfield(oo_,'PointForecast')
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var_names=fieldnames(oo_.PointForecast.HPDinf);
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moment_names=fieldnames(oo_.PointForecast);
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for moment_iter=1:length(moment_names)
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for var_iter=1:length(var_names)
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if strcmp(moment_names{moment_iter},'deciles')
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oo_.MeanForecast.(moment_names{moment_iter}).(var_names{var_iter})=...
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[oo_.SmoothedVariables.(moment_names{moment_iter}).(var_names{var_iter})(:,end)*ones(M_.maximum_endo_lag,1) oo_.MeanForecast.(moment_names{moment_iter}).(var_names{var_iter})];
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oo_.PointForecast.(moment_names{moment_iter}).(var_names{var_iter})=...
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[oo_.SmoothedVariables.(moment_names{moment_iter}).(var_names{var_iter})(:,end)*ones(M_.maximum_endo_lag,1) oo_.PointForecast.(moment_names{moment_iter}).(var_names{var_iter})];
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else
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oo_.MeanForecast.(moment_names{moment_iter}).(var_names{var_iter})=...
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[oo_.SmoothedVariables.(moment_names{moment_iter}).(var_names{var_iter})(end)*ones(M_.maximum_endo_lag,1); oo_.MeanForecast.(moment_names{moment_iter}).(var_names{var_iter})];
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oo_.PointForecast.(moment_names{moment_iter}).(var_names{var_iter})=...
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[oo_.SmoothedVariables.(moment_names{moment_iter}).(var_names{var_iter})(end)*ones(M_.maximum_endo_lag,1); oo_.PointForecast.(moment_names{moment_iter}).(var_names{var_iter})];
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end
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end
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end
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end
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%% change HPD-fields back to row vectors
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if isfield(oo_,'PointForecast') && isfield(oo_.PointForecast,'HPDinf')
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names=fieldnames(oo_.PointForecast.HPDinf);
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for ii=1:length(names)
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oo_.PointForecast.HPDinf.(names{ii})=oo_.PointForecast.HPDinf.(names{ii})';
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oo_.PointForecast.HPDsup.(names{ii})=oo_.PointForecast.HPDsup.(names{ii})';
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end
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end
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if isfield(oo_,'MeanForecast') && isfield(oo_.MeanForecast,'HPDinf')
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names=fieldnames(oo_.MeanForecast.HPDinf);
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for ii=1:length(names)
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oo_.MeanForecast.HPDinf.(names{ii})=oo_.MeanForecast.HPDinf.(names{ii})';
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oo_.MeanForecast.HPDsup.(names{ii})=oo_.MeanForecast.HPDsup.(names{ii})';
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end
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end
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if isfield(oo_,'UpdatedVariables') && isfield(oo_.UpdatedVariables,'HPDinf')
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names=fieldnames(oo_.UpdatedVariables.HPDinf);
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for ii=1:length(names)
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oo_.UpdatedVariables.HPDinf.(names{ii})=oo_.UpdatedVariables.HPDinf.(names{ii})';
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oo_.UpdatedVariables.HPDsup.(names{ii})=oo_.UpdatedVariables.HPDsup.(names{ii})';
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end
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end
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if isfield(oo_,'SmoothedVariables') && isfield(oo_.SmoothedVariables,'HPDinf')
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names=fieldnames(oo_.SmoothedVariables.HPDinf);
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for ii=1:length(names)
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oo_.SmoothedVariables.HPDinf.(names{ii})=oo_.SmoothedVariables.HPDinf.(names{ii})';
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oo_.SmoothedVariables.HPDsup.(names{ii})=oo_.SmoothedVariables.HPDsup.(names{ii})';
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end
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end
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if isfield(oo_,'FilteredVariables') && isfield(oo_.FilteredVariables,'HPDinf')
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names=fieldnames(oo_.FilteredVariables.HPDinf);
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for ii=1:length(names)
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oo_.FilteredVariables.HPDinf.(names{ii})=oo_.FilteredVariables.HPDinf.(names{ii})';
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oo_.FilteredVariables.HPDsup.(names{ii})=oo_.FilteredVariables.HPDsup.(names{ii})';
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end
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end
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if isfield(oo_,'SmoothedShocks') && isfield(oo_.SmoothedShocks,'HPDinf')
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names=fieldnames(oo_.SmoothedShocks.HPDinf);
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for ii=1:length(names)
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oo_.SmoothedShocks.HPDinf.(names{ii})=oo_.SmoothedShocks.HPDinf.(names{ii})';
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oo_.SmoothedShocks.HPDsup.(names{ii})=oo_.SmoothedShocks.HPDsup.(names{ii})';
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end
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end
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%% subtract mean from classical Updated variables
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if isfield(oo_,'UpdatedVariables')
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names=fieldnames(oo_.UpdatedVariables);
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for ii=1:length(names)
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%make sure Bayesian fields are not affected
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if ~strcmp(names{ii},'Mean') && ~strcmp(names{ii},'Median') && ~strcmp(names{ii},'deciles') ...
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&& ~strcmp(names{ii},'Var') && ~strcmp(names{ii},'HPDinf') && ~strcmp(names{ii},'HPDsup')
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current_var_index=find(strmatch(names{ii},deblank(M_.endo_names),'exact'));
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if options_.loglinear == 1 %logged steady state must be used
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constant_current_variable=log(oo_.dr.ys(current_var_index));
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elseif options_.loglinear == 0 %unlogged steady state must be used
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constant_current_variable=oo_.dr.ys(current_var_index);
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end
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oo_.UpdatedVariables.(names{ii})=oo_.UpdatedVariables.(names{ii})-constant_current_variable;
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if isfield(oo_.Smoother,'Trend') && isfield(oo_.Smoother.Trend,names{ii})
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oo_.UpdatedVariables.(names{ii})=oo_.UpdatedVariables.(names{ii})-oo_.Smoother.Trend.(names{ii});
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end
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end
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end
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end
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%% padd classical filtered variables with redundant zeros and subtract mean
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if isfield(oo_,'FilteredVariables')
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names=fieldnames(oo_.FilteredVariables);
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for ii=1:length(names)
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%make sure Bayesian fields are not affected
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if ~strcmp(names{ii},'Mean') && ~strcmp(names{ii},'Median') && ~strcmp(names{ii},'deciles') ...
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&& ~strcmp(names{ii},'Var') && ~strcmp(names{ii},'HPDinf') && ~strcmp(names{ii},'HPDsup')
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current_var_index=find(strmatch(names{ii},deblank(M_.endo_names),'exact'));
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if options_.loglinear == 1 %logged steady state must be used
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constant_current_variable=log(oo_.dr.ys(current_var_index));
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elseif options_.loglinear == 0 %unlogged steady state must be used
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constant_current_variable=oo_.dr.ys(current_var_index);
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end
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oo_.FilteredVariables.(names{ii})=oo_.FilteredVariables.(names{ii})-constant_current_variable;
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if isfield(oo_.Smoother,'Trend') && isfield(oo_.Smoother.Trend,names{ii})
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oo_.FilteredVariables.(names{ii})=oo_.FilteredVariables.(names{ii})-oo_.Smoother.Trend.(names{ii});
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end
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oo_.FilteredVariables.(names{ii})=[0; oo_.FilteredVariables.(names{ii}); zeros(options_.nk-1,1)];
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end
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end
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end
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%% resort fields that are in declaration order to decision rule order (previous undocumented behavior)
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if ~isempty(options_.nk) && options_.nk ~= 0 && ~isempty(bayestopt_)
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if ~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.pshape> 0) && options_.load_mh_file)) %no Bayesian estimation
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positions_in_decision_order=oo_.dr.inv_order_var(bayestopt_.smoother_var_list(bayestopt_.smoother_saved_var_list));
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if ~(options_.selected_variables_only && ~(options_.forecast > 0)) %happens only when selected_variables_only is not used
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oo_.FilteredVariablesKStepAhead(:,positions_in_decision_order,:)=oo_.FilteredVariablesKStepAhead;
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if ~isempty(PK) %get K-step ahead variances
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oo_.FilteredVariablesKStepAheadVariances(:,positions_in_decision_order,positions_in_decision_order,:)=oo_.FilteredVariablesKStepAheadVariances;
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end
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if ~isempty(decomp)
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oo_.FilteredVariablesShockDecomposition(:,positions_in_decision_order,:,:)=oo_.FilteredVariablesShockDecomposition;
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end
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else
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fprintf('\nconvert_dyn_45_to_44:: Due to a bug in Dynare 4.4.3 with the selected_variables_only option, the previous behavior\n')
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fprintf('convert_dyn_45_to_44:: cannot be restored for FilteredVariablesKStepAhead, FilteredVariablesKStepAheadVariances, and\n')
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fprintf('convert_dyn_45_to_44:: FilteredVariablesShockDecomposition\n')
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end
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end
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end
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if options_.filter_covariance
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oo_.Smoother.Variance(oo_.dr.inv_order_var,oo_.dr.inv_order_var,:)=oo_.Smoother.Variance;
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end
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%% set old field posterior_std and remove new field posterior_std_at_mode
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if isfield(oo_,'posterior_std_at_mode')
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oo_.posterior_std=oo_.posterior_std_at_mode;
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oo_=rmfield(oo_,'posterior_std_at_mode');
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end
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%Deal with OSR
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if ~isempty(M_.osr.variable_weights)
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evalin('base','optim_weights_=M_.osr.variable_weights')
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end
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if ~isempty(M_.osr.variable_indices)
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evalin('base','obj_var_=M_.osr.variable_indices')
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end
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if ~isempty(M_.osr.param_names)
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evalin('base','osr_params_=char(M_.osr.param_names)')
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end |