Various cosmetic fixes
parent
f07408a426
commit
6872d8b0d1
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@ -186,7 +186,7 @@ if isequal(options_.mode_compute,0) && isempty(options_.mode_file) && ~options_.
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if options_.occbin.smoother.status
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if options_.occbin.smoother.status
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[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp,Trend,state_uncertainty,M_,oo_,bayestopt_] = occbin.DSGE_smoother(xparam1,gend,transpose(data),data_index,missing_value,M_,oo_,options_,bayestopt_,estim_params_,dataset_,dataset_info);
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[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp,Trend,state_uncertainty,M_,oo_,bayestopt_] = occbin.DSGE_smoother(xparam1,gend,transpose(data),data_index,missing_value,M_,oo_,options_,bayestopt_,estim_params_,dataset_,dataset_info);
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else
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else
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[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp,Trend,state_uncertainty,M_,oo_,bayestopt_] = DsgeSmoother(xparam1,gend,transpose(data),data_index,missing_value,M_,oo_,options_,bayestopt_,estim_params_);
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[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp,Trend,state_uncertainty,M_,oo_,bayestopt_] = DsgeSmoother(xparam1,gend,transpose(data),data_index,missing_value,M_,oo_,options_,bayestopt_,estim_params_);
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end
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end
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[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);
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[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);
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end
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end
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@ -104,7 +104,7 @@ dynareParallelMkDir(RemoteTmpFolder,DataInput);
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ErrorCode=0;
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ErrorCode=0;
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for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
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for Node=1:length(DataInput) % To obtain a recursive function remove the 'for'
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% and use AnalyseComputationalEnvironment with differents input!
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% and use AnalyseComputationalEnvironment with differents input!
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@ -74,7 +74,7 @@ if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
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fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
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fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
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end
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end
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if options_.rplottype == 0
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if options_.rplottype == 0 %all in one plot
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hh=dyn_figure(options_.nodisplay,'Name', 'Simulated Trajectory');
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hh=dyn_figure(options_.nodisplay,'Name', 'Simulated Trajectory');
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plot(ix(i),y(:,i)) ;
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plot(ix(i),y(:,i)) ;
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if options_.TeX
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if options_.TeX
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@ -98,7 +98,7 @@ if options_.rplottype == 0
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if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
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if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
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create_TeX_loader(fidTeX,[M_.dname, '/graphs/', 'SimulatedTrajectory_' s1{1}],'Simulated trajectories','SimulatedTrajectory_',s1{1},1)
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create_TeX_loader(fidTeX,[M_.dname, '/graphs/', 'SimulatedTrajectory_' s1{1}],'Simulated trajectories','SimulatedTrajectory_',s1{1},1)
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end
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end
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elseif options_.rplottype == 1
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elseif options_.rplottype == 1 %separate figures each
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for j = 1:size(y,1)
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for j = 1:size(y,1)
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hh=dyn_figure(options_.nodisplay,'Name', 'Simulated Trajectory');
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hh=dyn_figure(options_.nodisplay,'Name', 'Simulated Trajectory');
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plot(ix(i),y(j,i)) ;
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plot(ix(i),y(j,i)) ;
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@ -114,7 +114,7 @@ elseif options_.rplottype == 1
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create_TeX_loader(fidTeX,[M_.dname, '/graphs/', 'SimulatedTrajectory_' s1{j}],'Simulated trajectories','SimulatedTrajectory_',s1{j},1);
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create_TeX_loader(fidTeX,[M_.dname, '/graphs/', 'SimulatedTrajectory_' s1{j}],'Simulated trajectories','SimulatedTrajectory_',s1{j},1);
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end
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end
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end
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end
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elseif options_.rplottype == 2
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elseif options_.rplottype == 2 %different subplots
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hh=dyn_figure(options_.nodisplay,'Name', 'Simulated Trajectory');
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hh=dyn_figure(options_.nodisplay,'Name', 'Simulated Trajectory');
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nl = max(1,fix(size(y,1)/4)) ;
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nl = max(1,fix(size(y,1)/4)) ;
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nc = ceil(size(y,1)/nl) ;
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nc = ceil(size(y,1)/nl) ;
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@ -1,5 +1,5 @@
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function [xparam1, estim_params_, bayestopt_, lb, ub, M_]=set_prior(estim_params_, M_, options_)
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function [xparam1, estim_params_, bayestopt_, lb, ub, M_]=set_prior(estim_params_, M_, options_)
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% function [xparam1,estim_params_,bayestopt_,lb,ub]=set_prior(estim_params_)
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% function [xparam1,estim_params_,bayestopt_,lb,ub, M_]=set_prior(estim_params_, M_, options_)
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% sets prior distributions
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% sets prior distributions
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%
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%
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% INPUTS
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% INPUTS
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