923 lines
41 KiB
Matlab
923 lines
41 KiB
Matlab
function [rmse_MC, ixx] = filt_mc_(OutDir,options_gsa_,dataset_,dataset_info,M_,oo_,options_,bayestopt_,estim_params_)
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% [rmse_MC, ixx] = filt_mc_(OutDir,options_gsa_,dataset_,dataset_info,M_,oo_,options_,bayestopt_,estim_params_
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% Inputs:
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% - OutputDirectoryName [string] name of the output directory
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% - options_gsa_ [structure] GSA options
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% - dataset_ [dseries] object storing the dataset
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% - dataset_info [structure] storing informations about the sample.
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% - M_ [structure] Matlab's structure describing the model
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% - oo_ [structure] storing the results
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% - options_ [structure] Matlab's structure describing the current options
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% - bayestopt_ [structure] describing the priors
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% - estim_params_ [structure] characterizing parameters to be estimated
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%
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% Outputs:
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% - rmse_MC [double] RMSE by nvar matrix of the RMSEs
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% - ixx [double] RMSE by nvar matrix of sorting
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% indices (descending order of RMSEs)
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% inputs (from opt_gsa structure)
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% vvarvecm = options_gsa_.var_rmse;
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% loadSA = options_gsa_.load_rmse;
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% pfilt = options_gsa_.pfilt_rmse;
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% alpha = options_gsa_.alpha_rmse;
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% alpha2 = options_gsa_.alpha2_rmse;
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% istart = options_gsa_.istart_rmse;
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%
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% Written by Marco Ratto
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% Joint Research Centre, The European Commission,
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% marco.ratto@ec.europa.eu
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% Copyright © 2012-2016 European Commission
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% Copyright © 2012-2023 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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vvarvecm = options_gsa_.var_rmse;
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if options_.TeX
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vvarvecm_tex = options_gsa_.var_rmse_tex;
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else
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vvarvecm_tex = {};
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end
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loadSA = options_gsa_.load_rmse;
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pfilt = options_gsa_.pfilt_rmse;
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alpha = options_gsa_.alpha_rmse;
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alpha2 = 0;
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pvalue = options_gsa_.alpha2_rmse;
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istart = max(2,options_gsa_.istart_rmse);
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fname_ = M_.fname;
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skipline(1)
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disp('Starting sensitivity analysis')
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disp('for the fit of EACH observed series ...')
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skipline()
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if ~options_.nograph
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disp('Deleting old SA figures...')
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a=dir([OutDir,filesep,'*.*']);
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tmp1='0';
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if options_.opt_gsa.ppost
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tmp='_rmse_post';
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else
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if options_.opt_gsa.pprior
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tmp='_rmse_prior';
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else
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tmp='_rmse_mc';
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end
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if options_gsa_.lik_only
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tmp1 = [tmp,'_post_SA'];
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tmp = [tmp,'_lik_SA'];
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end
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end
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for j=1:length(a)
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if strmatch([fname_,tmp],a(j).name)
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if options_.debug
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disp(a(j).name)
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end
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delete([OutDir,filesep,a(j).name])
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end
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if strmatch([fname_,tmp1],a(j).name)
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if options_.debug
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disp(a(j).name)
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end
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delete([OutDir,filesep,a(j).name])
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end
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end
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disp('done !')
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end
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[param_names,param_names_tex]=get_LaTeX_parameter_names(M_,options_,estim_params_,bayestopt_);
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nshock=estim_params_.nvx + estim_params_.nvn + estim_params_.ncx + estim_params_.ncn;
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npar=estim_params_.np;
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if ~isempty(options_.mode_file)
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load(options_.mode_file,'xparam1')
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end
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if options_.opt_gsa.ppost
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c=load([M_.dname filesep 'Output' filesep fname_,'_mean.mat'],'xparam1');
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xparam1_mean=c.xparam1;
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xparam1=c.xparam1;
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clear c
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elseif ~isempty(options_.mode_file) && exist([M_.dname filesep 'Output' filesep fname_,'_mean.mat'],'file')==2
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c=load([M_.dname filesep 'Output' filesep fname_,'_mean.mat'],'xparam1');
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xparam1_mean=c.xparam1;
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xparam1=c.xparam1;
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clear c
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end
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if options_.opt_gsa.ppost
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fnamtmp=[fname_,'_post'];
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DirectoryName = CheckPath('metropolis',M_.dname);
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else
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if options_.opt_gsa.pprior
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fnamtmp=[fname_,'_prior'];
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DirectoryName = CheckPath(['gsa' filesep 'prior'],M_.dname);
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else
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fnamtmp=[fname_,'_mc'];
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DirectoryName = CheckPath(['gsa' filesep 'mc'],M_.dname);
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end
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end
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if loadSA
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tmplist =load([OutDir,filesep,fnamtmp, '.mat'],'vvarvecm');
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if isempty(fieldnames(tmplist))
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disp('WARNING: cannot load results since the list of variables used is not present in the mat file')
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loadSA=0;
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elseif ~isequal(tmplist.vvarvecm,vvarvecm)
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disp('WARNING: cannot load results since the list of variables in the mat file differs from the one requested.')
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loadSA=0;
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end
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end
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if ~loadSA
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Y = transpose(dataset_.data);
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gend = dataset_.nobs;
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data_index = dataset_info.missing.aindex;
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missing_value = dataset_info.missing.state;
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filfilt = dir([DirectoryName filesep M_.fname '_filter_step_ahead*.mat']);
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filupdate = dir([DirectoryName filesep M_.fname '_update*.mat']);
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filparam = dir([DirectoryName filesep M_.fname '_param*.mat']);
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x=[];
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logpo2=[];
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sto_ys=[];
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for j=1:length(filparam)
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if isempty(strmatch([M_.fname '_param_irf'],filparam(j).name))
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temp=load([DirectoryName filesep filparam(j).name]); % from prior_posterior_statistics_core
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x=[x; temp.stock];
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logpo2=[logpo2; temp.stock_logpo];
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sto_ys=[sto_ys; temp.stock_ys];
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clear temp;
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end
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end
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nruns=size(x,1);
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nfilt=floor(pfilt*nruns);
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if options_.opt_gsa.ppost || (options_.opt_gsa.ppost==0 && options_.opt_gsa.lik_only==0)
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skipline()
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disp('Computing RMSE''s...')
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jxj=NaN(length(vvarvecm),1);
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js=NaN(length(vvarvecm),1);
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yss=NaN(length(vvarvecm),gend,size(sto_ys,1));
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for i = 1:length(vvarvecm)
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vj = vvarvecm{i};
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jxj(i) = strmatch(vj, M_.endo_names(oo_.dr.order_var), 'exact');
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js(i) = strmatch(vj, M_.endo_names, 'exact');
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yss(i,:,:)=repmat(sto_ys(:,js(i))',[gend,1]);
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end
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if exist('xparam1','var')
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[~,~,~,ahat,~,~,aK] = DsgeSmoother(xparam1,gend,Y,data_index,missing_value,M_,oo_,options_,bayestopt_,estim_params_);
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y0 = reshape( squeeze(aK(1,jxj,1:gend)),[gend length(jxj)]);
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yobs = transpose( ahat(jxj,:));
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rmse_mode = sqrt(mean((yobs(istart:end,:)-y0(istart:end,:)).^2));
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r2_mode = 1-sum((yobs(istart:end,:)-y0(istart:end,:)).^2)./sum(yobs(istart:end,:).^2);
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end
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y0=-yss; %demean everything using the theoretical mean, i.e. steady state
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nbb=0;
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for j=1:length(filfilt)
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temp=load([DirectoryName filesep M_.fname '_filter_step_ahead',num2str(j),'.mat']);
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nb = size(temp.stock,4);
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y0(:,:,nbb+1:nbb+nb)=y0(:,:,nbb+1:nbb+nb)+reshape(temp.stock(1,js,1:gend,:),[length(js) gend nb]);
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nbb=nbb+nb;
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clear temp;
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end
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yobs=-yss;
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nbb=0;
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for j=1:length(filupdate)
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temp=load([DirectoryName filesep M_.fname '_update',num2str(j),'.mat']);
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nb = size(temp.stock,3);
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yobs(:,:,nbb+1:nbb+nb)=yobs(:,:,nbb+1:nbb+nb)+reshape(temp.stock(js,1:gend,:),[length(js) gend nb]);
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nbb=nbb+nb;
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clear temp;
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end
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rmse_MC=zeros(nruns,length(js));
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r2_MC=zeros(nruns,length(js));
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for j=1:nruns
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rmse_MC(j,:) = sqrt(mean((yobs(:,istart:end,j)'-y0(:,istart:end,j)').^2));
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r2_MC(j,:) = 1-mean((yobs(:,istart:end,j)'-y0(:,istart:end,j)').^2)./mean((yobs(:,istart:end,j)').^2);
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end
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if exist('xparam1_mean','var')
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[~,~,~,ahat,~,~,aK] = DsgeSmoother(xparam1_mean,gend,Y,data_index,missing_value,M_,oo_,options_,bayestopt_,estim_params_);
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y0 = reshape( squeeze(aK(1,jxj,1:gend)),[gend length(jxj)]);
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yobs = transpose( ahat(jxj,:));
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rmse_pmean = sqrt(mean((yobs(istart:end,:)-y0(istart:end,:)).^2));
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r2_pmean = 1-mean((yobs(istart:end,:)-y0(istart:end,:)).^2)./mean(yobs(istart:end,:).^2);
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end
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clear stock_filter;
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end
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lnprior=NaN(nruns,1);
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for j=1:nruns
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lnprior(j,1) = priordens(x(j,:)',bayestopt_.pshape,bayestopt_.p6,bayestopt_.p7,bayestopt_.p3,bayestopt_.p4);
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end
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likelihood=logpo2(:)-lnprior(:);
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disp('... done!')
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if options_.opt_gsa.ppost
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save([OutDir,filesep,fnamtmp,'.mat'], 'x', 'logpo2', 'likelihood', 'rmse_MC', 'r2_MC', 'vvarvecm')
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if exist('xparam1_mean','var')
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save([OutDir,filesep,fnamtmp, '.mat'], 'rmse_pmean', 'r2_pmean','-append')
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end
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if exist('xparam1','var')
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save([OutDir,filesep,fnamtmp,'.mat'], 'rmse_mode', 'r2_mode','-append')
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end
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else
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if options_.opt_gsa.lik_only
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save([OutDir,filesep,fnamtmp, '.mat'], 'x', 'logpo2','likelihood', '-append')
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else
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save([OutDir,filesep,fnamtmp, '.mat'], 'x', 'logpo2','likelihood', 'rmse_MC', 'r2_MC', 'vvarvecm','-append')
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if exist('xparam1_mean','var')
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save([OutDir,filesep,fnamtmp, '.mat'], 'rmse_pmean', 'r2_pmean','-append')
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end
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if exist('xparam1','var')
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save([OutDir,filesep,fnamtmp,'.mat'], 'rmse_mode', 'r2_mode','-append')
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end
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end
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end
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else % loadSA
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if options_.opt_gsa.lik_only && options_.opt_gsa.ppost==0
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load([OutDir,filesep,fnamtmp, '.mat'],'x','logpo2','likelihood');
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else
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load([OutDir,filesep,fnamtmp, '.mat'],'x','logpo2','likelihood','rmse_MC','rmse_mode','rmse_pmean', 'r2_MC', 'vvarvecm', 'r2_mode','r2_pmean');
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end
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lnprior=logpo2(:)-likelihood(:);
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nruns=size(x,1);
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nfilt=floor(pfilt*nruns);
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end
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% Smirnov tests
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nfilt0 = nfilt*ones(length(vvarvecm), 1);
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logpo2=logpo2(:);
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if ~options_.opt_gsa.ppost
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[~, ipost]=sort(-logpo2);
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[~, ilik]=sort(-likelihood);
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end
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% visual scatter analysis!
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if options_.opt_gsa.ppost
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tmp_title='R2 Scatter plot: Posterior';
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atitle='R2 Scatter plot: Posterior';
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asname='r2_post';
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else
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if options_.opt_gsa.pprior
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tmp_title='R2 Scatter plot: Prior';
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atitle='R2 Scatter plot: Prior';
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asname='r2_prior';
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else
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tmp_title='R2 Scatter plot: MC';
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atitle='R2 Scatter plot: MC';
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asname='r2_mc';
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end
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end
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options_scatter.param_names = vvarvecm;
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options_scatter.param_names_tex = vvarvecm_tex;
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options_scatter.fname_ = fname_;
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options_scatter.OutputDirectoryName = OutDir;
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options_scatter.amcf_name = asname;
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options_scatter.amcf_title = atitle;
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options_scatter.title = tmp_title;
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scatter_analysis(r2_MC, x,options_scatter, options_);
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% end of visual scatter analysis
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if ~options_.opt_gsa.ppost && options_.opt_gsa.lik_only
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if options_.opt_gsa.pprior
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anam='rmse_prior_post';
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atitle='RMSE prior: Log Posterior Kernel';
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else
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anam='rmse_mc_post';
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atitle='RMSE MC: Log Posterior Kernel';
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end
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options_mcf.pvalue_ks = alpha;
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options_mcf.pvalue_corr = pvalue;
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options_mcf.alpha2 = alpha2;
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options_mcf.param_names = param_names;
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if options_.TeX
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options_mcf.param_names_tex = param_names_tex;
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else
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options_mcf.param_names_tex = {};
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end
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options_mcf.fname_ = fname_;
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options_mcf.OutputDirectoryName = OutDir;
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options_mcf.amcf_name = anam;
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options_mcf.amcf_title = atitle;
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options_mcf.title = atitle;
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options_mcf.beha_title = 'better posterior kernel';
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options_mcf.nobeha_title = 'worse posterior kernel';
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if options_.TeX
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options_mcf.beha_title_latex = 'better posterior kernel';
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options_mcf.nobeha_title_latex = 'worse posterior kernel';
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end
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mcf_analysis(x, ipost(1:nfilt), ipost(nfilt+1:end), options_mcf, M_, options_, bayestopt_, estim_params_);
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if options_.opt_gsa.pprior
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anam = 'rmse_prior_lik';
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atitle = 'RMSE prior: Log Likelihood Kernel';
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else
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anam='rmse_mc_lik';
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atitle = 'RMSE MC: Log Likelihood Kernel';
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end
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options_mcf.amcf_name = anam;
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options_mcf.amcf_title = atitle;
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options_mcf.title = atitle;
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options_mcf.beha_title = 'better likelihood';
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options_mcf.nobeha_title = 'worse likelihood';
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if options_.TeX
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options_mcf.beha_title_latex = 'better likelihood';
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options_mcf.nobeha_title_latex = 'worse likelihood';
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end
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mcf_analysis(x, ilik(1:nfilt), ilik(nfilt+1:end), options_mcf, M_, options_, bayestopt_, estim_params_);
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else
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if options_.opt_gsa.ppost
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rmse_txt=rmse_pmean;
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r2_txt=r2_pmean;
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else
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if options_.opt_gsa.pprior || ~exist('rmse_pmean','var')
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if exist('rmse_mode','var')
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rmse_txt=rmse_mode;
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r2_txt=r2_mode;
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else
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rmse_txt=NaN(1,size(rmse_MC,2));
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r2_txt=NaN(1,size(r2_MC,2));
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end
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else
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rmse_txt=rmse_pmean;
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r2_txt=r2_pmean;
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end
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end
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ixx=NaN(size(rmse_MC,1),length(vvarvecm));
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for i = 1:length(vvarvecm)
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[~, ixx(:,i)] = sort(rmse_MC(:,i));
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end
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PP = ones(npar+nshock, length(vvarvecm));
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PPV = ones(length(vvarvecm), length(vvarvecm), npar+nshock);
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SS = zeros(npar+nshock, length(vvarvecm));
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for j = 1:npar+nshock
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for i = 1:length(vvarvecm)
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[~, P] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j), alpha);
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[H1] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,1);
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[H2] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,-1);
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if H1==0 && H2==0
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SS(j,i)=1;
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elseif H1==0
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SS(j,i)=-1;
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else
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SS(j,i)=0;
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end
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PP(j,i)=P;
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end
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for i = 1:length(vvarvecm)
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for l = 1:length(vvarvecm)
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if l~=i && PP(j,i)<alpha && PP(j,l)<alpha
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[~,P] = smirnov(x(ixx(1:nfilt0(i),i),j),x(ixx(1:nfilt0(l),l),j), alpha);
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PPV(i,l,j) = P;
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elseif l==i
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PPV(i,l,j) = PP(j,i);
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end
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end
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end
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end
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if ~options_.nograph
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ifig=0;
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for i=1:length(vvarvecm)
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if options_.opt_gsa.ppost
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temp_name='RMSE Posterior: Log Prior';
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else
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if options_.opt_gsa.pprior
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temp_name='RMSE Prior: Log Prior';
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else
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temp_name='RMSE MC: Log Prior';
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end
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end
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if mod(i,9)==1
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ifig=ifig+1;
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hh_fig=dyn_figure(options_.nodisplay,'name',[temp_name,' ',int2str(ifig)]);
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end
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subplot(3,3,i-9*(ifig-1))
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h=cumplot(lnprior(ixx(1:nfilt0(i),i)));
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set(h,'color','blue','linewidth',2)
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hold on, h=cumplot(lnprior);
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set(h,'color','k','linewidth',1)
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h=cumplot(lnprior(ixx(nfilt0(i)+1:end,i)));
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set(h,'color','red','linewidth',2)
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|
if options_.TeX
|
|
title(vvarvecm_tex{i},'interpreter','latex')
|
|
else
|
|
title(vvarvecm{i},'interpreter','none')
|
|
end
|
|
if mod(i,9)==0 || i==length(vvarvecm)
|
|
if ~isoctave
|
|
annotation('textbox', [0.1,0,0.35,0.05],'String', 'Log-prior for BETTER R2','Color','Blue','horizontalalignment','center');
|
|
annotation('textbox', [0.55,0,0.35,0.05],'String', 'Log-prior for WORSE R2', 'Color','Red','horizontalalignment','center');
|
|
end
|
|
if options_.opt_gsa.ppost
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_post_lnprior',int2str(ifig)],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir '/' fname_ '_rmse_post_lnprior',int2str(ifig)],ifig,[temp_name,' ',int2str(ifig)],'rmse_post_lnprior',options_.figures.textwidth*min((i-9*(ifig-1))/3,1))
|
|
end
|
|
else
|
|
if options_.opt_gsa.pprior
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_prior_lnprior',int2str(ifig) ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir '/' fname_ '_rmse_prior_lnprior',int2str(ifig)],ifig,[temp_name,' ',int2str(ifig)],'rmse_prior_lnprior',options_.figures.textwidth*min((i-9*(ifig-1))/3,1))
|
|
end
|
|
else
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_mc_lnprior',int2str(ifig) ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir '/' fname_ '_rmse_mc_lnprior',int2str(ifig)],ifig,[temp_name,' ',int2str(ifig)],'rmse_mc_lnprior',options_.figures.textwidth*min((i-9*(ifig-1))/3,1))
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|
|
ifig=0;
|
|
for i=1:length(vvarvecm)
|
|
if options_.opt_gsa.ppost
|
|
temp_name='RMSE Posterior: Log Likelihood';
|
|
else
|
|
if options_.opt_gsa.pprior
|
|
temp_name='RMSE Prior: Log Likelihood';
|
|
else
|
|
temp_name='RMSE MC: Log Likelihood';
|
|
end
|
|
end
|
|
if mod(i,9)==1
|
|
ifig=ifig+1;
|
|
hh_fig = dyn_figure(options_.nodisplay,'Name',[temp_name,' ',int2str(ifig)]);
|
|
end
|
|
subplot(3,3,i-9*(ifig-1))
|
|
h=cumplot(likelihood(ixx(1:nfilt0(i),i)));
|
|
set(h,'color','blue','linewidth',2)
|
|
hold on, h=cumplot(likelihood);
|
|
set(h,'color','k','linewidth',1)
|
|
h=cumplot(likelihood(ixx(nfilt0(i)+1:end,i)));
|
|
set(h,'color','red','linewidth',2)
|
|
if options_.TeX
|
|
title(vvarvecm_tex{i},'interpreter','latex')
|
|
else
|
|
title(vvarvecm{i},'interpreter','none')
|
|
end
|
|
if options_.opt_gsa.ppost==0
|
|
set(gca,'xlim',[min( likelihood(ixx(1:nfilt0(i),i)) ) max( likelihood(ixx(1:nfilt0(i),i)) )])
|
|
end
|
|
if mod(i,9)==0 || i==length(vvarvecm)
|
|
if ~isoctave
|
|
annotation('textbox', [0.1,0,0.35,0.05],'String', 'Log-likelihood for BETTER R2','Color','Blue','horizontalalignment','center');
|
|
annotation('textbox', [0.55,0,0.35,0.05],'String', 'Log-likelihood for WORSE R2', 'Color','Red','horizontalalignment','center');
|
|
end
|
|
if options_.opt_gsa.ppost
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_post_lnlik',int2str(ifig) ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_post_lnprior',int2str(ifig)],ifig,[temp_name,' ',int2str(ifig)],'rmse_post_lnprior',options_.figures.textwidth*min((i-9*(ifig-1))/3,1));
|
|
end
|
|
else
|
|
if options_.opt_gsa.pprior
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_prior_lnlik',int2str(ifig)],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_prior_lnlik',int2str(ifig)],ifig,[temp_name,' ',int2str(ifig)],'rmse_prior_lnlik',options_.figures.textwidth*min((i-9*(ifig-1))/3,1));
|
|
end
|
|
else
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_mc_lnlik',int2str(ifig) ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_mc_lnlik',int2str(ifig) ],ifig,[temp_name,' ',int2str(ifig)],'rmse_mc_lnlik',options_.figures.textwidth*min((i-9*(ifig-1))/3,1));
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|
|
ifig=0;
|
|
for i=1:length(vvarvecm)
|
|
if options_.opt_gsa.ppost
|
|
temp_name='RMSE Posterior: Log Posterior';
|
|
else
|
|
if options_.opt_gsa.pprior
|
|
temp_name='RMSE Prior: Log Posterior';
|
|
else
|
|
temp_name='RMSE MC: Log Posterior';
|
|
end
|
|
end
|
|
if mod(i,9)==1
|
|
ifig=ifig+1;
|
|
hh_fig = dyn_figure(options_.nodisplay,'Name',[temp_name,' ',int2str(ifig)]);
|
|
end
|
|
subplot(3,3,i-9*(ifig-1))
|
|
h=cumplot(logpo2(ixx(1:nfilt0(i),i)));
|
|
set(h,'color','blue','linewidth',2)
|
|
hold on, h=cumplot(logpo2);
|
|
set(h,'color','k','linewidth',1)
|
|
h=cumplot(logpo2(ixx(nfilt0(i)+1:end,i)));
|
|
set(h,'color','red','linewidth',2)
|
|
if options_.TeX
|
|
title(vvarvecm_tex{i},'interpreter','latex')
|
|
else
|
|
title(vvarvecm{i},'interpreter','none')
|
|
end
|
|
if options_.opt_gsa.ppost==0
|
|
set(gca,'xlim',[min( logpo2(ixx(1:nfilt0(i),i)) ) max( logpo2(ixx(1:nfilt0(i),i)) )])
|
|
end
|
|
if mod(i,9)==0 || i==length(vvarvecm)
|
|
if ~isoctave
|
|
annotation('textbox', [0.1,0,0.35,0.05],'String', 'Log-posterior for BETTER R2','Color','Blue','horizontalalignment','center');
|
|
annotation('textbox', [0.55,0,0.35,0.05],'String', 'Log-posterior for WORSE R2', 'Color','Red','horizontalalignment','center');
|
|
end
|
|
if options_.opt_gsa.ppost
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_post_lnpost',int2str(ifig) ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_post_lnpost',int2str(ifig) ],ifig,[temp_name,' ',int2str(ifig)],'rmse_post_lnpost',options_.figures.textwidth*min((i-9*(ifig-1))/3,1));
|
|
end
|
|
else
|
|
if options_.opt_gsa.pprior
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_prior_lnpost',int2str(ifig)],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_prior_lnpost',int2str(ifig)],ifig,[temp_name,' ',int2str(ifig)],'rmse_prior_lnpost',options_.figures.textwidth*min((i-9*(ifig-1))/3,1));
|
|
end
|
|
else
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_mc_lnpost',int2str(ifig)],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_mc_lnpost',int2str(ifig)],ifig,[temp_name,' ',int2str(ifig)],'rmse_mc_lnpost',options_.figures.textwidth*min((i-9*(ifig-1))/3,1));
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|
|
skipline()
|
|
title_string='RMSE over the MC sample:';
|
|
data_mat=[min(rmse_MC)' max(rmse_MC)'];
|
|
headers={'Variable'; 'min yr RMSE'; 'max yr RMSE'};
|
|
dyntable(options_, title_string, headers, vvarvecm, data_mat, 0, 15, 5);
|
|
if options_.TeX
|
|
headers_tex = {'\text{Variable}'; '\text{min yr RMSE}'; '\text{max yr RMSE}'};
|
|
dyn_latex_table(M_, options_, title_string, 'RMSE_MC', headers_tex, vvarvecm_tex, data_mat, 0, 15, 5);
|
|
end
|
|
invar = find( std(rmse_MC)./mean(rmse_MC)<=0.0001 );
|
|
if ~isempty(invar)
|
|
skipline(1)
|
|
disp('RMSE is not varying significantly over the MC sample for the following variables:')
|
|
disp(vvarvecm{invar})
|
|
disp('These variables are excluded from SA')
|
|
disp('[Unless you treat these series as exogenous, there is something wrong in your estimation !]')
|
|
end
|
|
vvarvecm0=vvarvecm;
|
|
ivar = find( std(rmse_MC)./mean(rmse_MC)>0.0001 );
|
|
vvarvecm = vvarvecm(ivar);
|
|
rmse_MC = rmse_MC(:,ivar);
|
|
skipline()
|
|
disp(['Sample filtered the ',num2str(pfilt*100),'% best RMSE''s for each observed series ...' ])
|
|
skipline(1)
|
|
title_string='RMSE ranges after filtering:';
|
|
if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior
|
|
headers = {'Variable'; 'min'; 'max'; 'min'; 'max'; 'posterior mode'};
|
|
headers_tex = {'\text{Variable}'; '\text{min}'; '\text{max}'; '\text{min}'; '\text{max}'; '\text{posterior mode}'};
|
|
else
|
|
headers = {'Variable'; 'min'; 'max'; 'min'; 'max'; 'posterior mean'};
|
|
headers_tex = {'\text{Variable}'; '\text{min}'; '\text{max}'; '\text{min}'; '\text{max}'; '\text{posterior mean}'};
|
|
end
|
|
data_mat=NaN(length(vvarvecm),5);
|
|
for j = 1:length(vvarvecm)
|
|
data_mat(j,:)=[min(rmse_MC(ixx(1:nfilt0(j),j),j)) ...
|
|
max(rmse_MC(ixx(1:nfilt0(j),j),j)) ...
|
|
min(rmse_MC(ixx(nfilt0(j)+1:end,j),j)) ...
|
|
max(rmse_MC(ixx(nfilt0(j)+1:end,j),j)) ...
|
|
rmse_txt(j)];
|
|
end
|
|
%get formatting for additional header line
|
|
val_width = 15;
|
|
val_precis = 5;
|
|
label_width = max(cellofchararraymaxlength(vertcat(headers{1}, vvarvecm))+2, 0);
|
|
label_format_leftbound = sprintf('%%-%ds', label_width);
|
|
if all(~isfinite(data_mat))
|
|
values_length = 4;
|
|
else
|
|
values_length = max(ceil(max(max(log10(abs(data_mat(isfinite(data_mat))))))),1)+val_precis+1;
|
|
end
|
|
if any(data_mat < 0) %add one character for minus sign
|
|
values_length = values_length+1;
|
|
end
|
|
headers_length = cellofchararraymaxlength(headers(2:end));
|
|
if ~isempty(val_width)
|
|
val_width = max(max(headers_length,values_length)+2, val_width);
|
|
else
|
|
val_width = max(headers_length, values_length)+2;
|
|
end
|
|
header_string_format = sprintf('%%%ds',val_width);
|
|
if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior
|
|
optional_header=sprintf([label_format_leftbound,header_string_format,header_string_format,header_string_format,header_string_format],'','',['best ',num2str(pfilt*100),'% filtered'],'','remaining 90%');
|
|
else
|
|
optional_header=sprintf([label_format_leftbound,header_string_format,header_string_format,header_string_format,header_string_format],'','','best filtered','','remaining');
|
|
end
|
|
dyntable(options_, title_string, headers, vvarvecm, data_mat, 0, val_width, val_precis,optional_header);
|
|
if options_.TeX
|
|
if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior
|
|
optional_header={[' & \multicolumn{2}{c}{best ',num2str(pfilt*100),' filtered} & \multicolumn{2}{c}{remaining 90\%}\\']};
|
|
else
|
|
optional_header={' & \multicolumn{2}{c}{best filtered} & \multicolumn{2}{c}{remaining}\\'};
|
|
end
|
|
dyn_latex_table(M_, options_, title_string, 'RMSE_ranges_after_filtering', headers_tex, vvarvecm_tex, data_mat, 0, val_width, val_precis, optional_header);
|
|
end
|
|
% R2 table
|
|
vvarvecm=vvarvecm0;
|
|
skipline()
|
|
title_string='R2 over the MC sample:';
|
|
data_mat=[min(r2_MC)' max(r2_MC)'];
|
|
headers = {'Variable'; 'min yr R2'; 'max yr R2'};
|
|
dyntable(options_, title_string, headers, vvarvecm, data_mat, 0, 15, 5);
|
|
if options_.TeX
|
|
headers_tex = {'\text{Variable}'; '\text{min yr R2}'; '\text{max yr R2}'};
|
|
dyn_latex_table(M_, options_, title_string, 'R2_MC', headers_tex, vvarvecm_tex, data_mat, 0, 15, 5);
|
|
end
|
|
r2_MC=r2_MC(:,ivar);
|
|
vvarvecm=vvarvecm(ivar);
|
|
skipline()
|
|
disp(['Sample filtered the ',num2str(pfilt*100),'% best R2''s for each observed series ...' ])
|
|
skipline()
|
|
disp('R2 ranges after filtering:')
|
|
title_string='R2 ranges after filtering:';
|
|
if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior
|
|
headers = {'Variable'; 'min'; 'max'; 'min'; 'max'; 'posterior mode'};
|
|
headers_tex = {'\text{Variable}'; '\text{min}'; '\text{max}'; '\text{min}'; '\text{max}'; '\text{posterior mode}'};
|
|
else
|
|
headers = {'Variable'; 'min'; 'max'; 'min'; 'max'; 'posterior mean'};
|
|
headers_tex = {'\text{Variable}'; '\text{min}'; '\text{max}'; '\text{min}'; '\text{max}'; '\text{posterior mean}'};
|
|
end
|
|
data_mat=NaN(length(vvarvecm),5);
|
|
for j = 1:length(vvarvecm)
|
|
data_mat(j,:)=[min(r2_MC(ixx(1:nfilt0(j),j),j)) ...
|
|
max(r2_MC(ixx(1:nfilt0(j),j),j)) ...
|
|
min(r2_MC(ixx(nfilt0(j)+1:end,j),j)) ...
|
|
max(r2_MC(ixx(nfilt0(j)+1:end,j),j)) ...
|
|
r2_txt(j)];
|
|
end
|
|
%get formatting for additional header line
|
|
val_width = 15;
|
|
val_precis = 5;
|
|
label_width = max(cellofchararraymaxlength(vertcat(headers{1}, vvarvecm))+2, 0);
|
|
label_format_leftbound = sprintf('%%-%ds', label_width);
|
|
if all(~isfinite(data_mat))
|
|
values_length = 4;
|
|
else
|
|
values_length = max(ceil(max(max(log10(abs(data_mat(isfinite(data_mat))))))),1)+val_precis+1;
|
|
end
|
|
if any(data_mat < 0) %add one character for minus sign
|
|
values_length = values_length+1;
|
|
end
|
|
headers_length = cellofchararraymaxlength(headers(2:end));
|
|
if ~isempty(val_width)
|
|
val_width = max(max(headers_length, values_length)+2, val_width);
|
|
else
|
|
val_width = max(headers_length, values_length)+2;
|
|
end
|
|
header_string_format = sprintf('%%%ds',val_width);
|
|
|
|
if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior
|
|
optional_header = sprintf([label_format_leftbound,header_string_format,header_string_format,header_string_format,header_string_format],'','',['best ',num2str(pfilt*100),'% filtered'],'','remaining 90%');
|
|
else
|
|
optional_header = sprintf([label_format_leftbound,header_string_format,header_string_format,header_string_format,header_string_format],'','','best filtered','','remaining');
|
|
end
|
|
dyntable(options_, title_string, headers, vvarvecm, data_mat, 0, val_width, val_precis, optional_header);
|
|
if options_.TeX
|
|
if ~options_.opt_gsa.ppost && options_.opt_gsa.pprior
|
|
optional_header = {[' & \multicolumn{2}{c}{best ',num2str(pfilt*100),' filtered} & \multicolumn{2}{c}{remaining 90\%}\\']};
|
|
else
|
|
optional_header = {' & \multicolumn{2}{c}{best filtered} & \multicolumn{2}{c}{remaining}\\'};
|
|
end
|
|
dyn_latex_table(M_, options_, title_string, 'R2_ranges_after_filtering', headers_tex, vvarvecm_tex, data_mat, 0, val_width, val_precis, optional_header);
|
|
end
|
|
% R2 table
|
|
SP = zeros(npar+nshock, length(vvarvecm));
|
|
for j = 1:length(vvarvecm)
|
|
ns=find(PP(:,j)<alpha);
|
|
SP(ns,j)=ones(size(ns));
|
|
SS(:,j)=SS(:,j).*SP(:,j);
|
|
end
|
|
nsp=NaN(npar+nshock,1);
|
|
for j=1:npar+nshock
|
|
nsp(j)=length(find(SP(j,:)));
|
|
end
|
|
snam0=param_names(nsp==0);
|
|
snam1=param_names(nsp==1);
|
|
snam2=param_names(nsp>1);
|
|
nsnam=(find(nsp>1));
|
|
skipline(1)
|
|
disp('These parameters do not affect significantly the fit of ANY observed series:')
|
|
disp(char(snam0))
|
|
skipline()
|
|
disp('These parameters affect ONE single observed series:')
|
|
disp(char(snam1))
|
|
skipline()
|
|
disp('These parameters affect MORE THAN ONE observed series: trade off exists!')
|
|
disp(char(snam2))
|
|
% plot trade-offs
|
|
if ~options_.nograph
|
|
a00=jet(length(vvarvecm));
|
|
if options_.opt_gsa.ppost
|
|
temp_name='RMSE Posterior Tradeoffs:';
|
|
atitle='RMSE Posterior Map:';
|
|
asname='rmse_post';
|
|
else
|
|
if options_.opt_gsa.pprior
|
|
temp_name='RMSE Prior Tradeoffs:';
|
|
atitle='RMSE Prior Map:';
|
|
asname='rmse_prior';
|
|
else
|
|
temp_name='RMSE MC Tradeoffs:';
|
|
atitle='RMSE MC Map:';
|
|
asname='rmse_mc';
|
|
end
|
|
end
|
|
% now I plot by observed variables
|
|
options_mcf.pvalue_ks = alpha;
|
|
options_mcf.pvalue_corr = pvalue;
|
|
options_mcf.alpha2 = alpha2;
|
|
options_mcf.param_names = param_names;
|
|
options_mcf.param_names_tex = param_names_tex;
|
|
options_mcf.fname_ = fname_;
|
|
options_mcf.OutputDirectoryName = OutDir;
|
|
for iy = 1:length(vvarvecm)
|
|
options_mcf.amcf_name = [asname '_' vvarvecm{iy} '_map' ];
|
|
options_mcf.amcf_title = [atitle ' ' vvarvecm{iy}];
|
|
options_mcf.beha_title = ['better fit of ' vvarvecm{iy}];
|
|
options_mcf.nobeha_title = ['worse fit of ' vvarvecm{iy}];
|
|
if options_.TeX
|
|
options_mcf.beha_title_latex = ['better fit of ' vvarvecm_tex{iy}];
|
|
options_mcf.nobeha_title_latex = ['worse fit of ' vvarvecm_tex{iy}];
|
|
end
|
|
options_mcf.title = ['the fit of ' vvarvecm{iy}];
|
|
mcf_analysis(x, ixx(1:nfilt0(iy),iy), ixx(nfilt0(iy)+1:end,iy), options_mcf, M_, options_, bayestopt_, estim_params_);
|
|
end
|
|
for iy = 1:length(vvarvecm)
|
|
ipar = find(any(squeeze(PPV(iy,:,:))<alpha));
|
|
for ix=1:ceil(length(ipar)/5)
|
|
hh_fig = dyn_figure(options_.nodisplay,'name',[temp_name,' observed variable ', vvarvecm{iy}]);
|
|
for j=1+5*(ix-1):min(length(ipar),5*ix)
|
|
subplot(2,3,j-5*(ix-1))
|
|
h0=cumplot(x(:,ipar(j)));
|
|
set(h0,'color',[0 0 0])
|
|
hold on,
|
|
iobs=find(squeeze(PPV(iy,:,ipar(j)))<alpha);
|
|
for i = 1:length(vvarvecm)
|
|
if any(iobs==i) || i==iy
|
|
h0=cumplot(x(ixx(1:nfilt0(i),i),ipar(j)));
|
|
if ~isoctave
|
|
hcmenu = uicontextmenu;
|
|
uimenu(hcmenu,'Label',vvarvecm{i});
|
|
set(h0,'uicontextmenu',hcmenu)
|
|
end
|
|
else
|
|
h0=cumplot(x(ixx(1:nfilt0(i),i),ipar(j))*NaN);
|
|
end
|
|
set(h0,'color',a00(i,:),'linewidth',2)
|
|
end
|
|
ydum=get(gca,'ylim');
|
|
if exist('xparam1','var')
|
|
xdum=xparam1(ipar(j));
|
|
h1=plot([xdum xdum],ydum);
|
|
set(h1,'color',[0.85 0.85 0.85],'linewidth',2)
|
|
end
|
|
xlabel('')
|
|
if options_.TeX
|
|
title([param_names_tex{ipar(j)}],'interpreter','latex')
|
|
else
|
|
title([param_names{ipar(j)}],'interpreter','none')
|
|
end
|
|
end
|
|
if isoctave
|
|
legend(vertcat('base',vvarvecm),'location','eastoutside');
|
|
else
|
|
if options_.TeX
|
|
h0=legend(vertcat('base',vvarvecm_tex),'interpreter','latex');
|
|
else
|
|
h0=legend(vertcat('base',vvarvecm),'interpreter','none');
|
|
end
|
|
set(h0,'fontsize',6,'position',[0.7 0.1 0.2 0.3]);
|
|
end
|
|
if options_.opt_gsa.ppost
|
|
dyn_saveas(hh_fig,[ OutDir filesep fname_ '_rmse_post_' vvarvecm{iy} '_' int2str(ix)],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[ OutDir filesep fname_ '_rmse_post_' vvarvecm{iy} '_' int2str(ix)],ix,[temp_name,' observed variable ',vvarvecm_tex{iy} ],['rmse_post_' vvarvecm{iy}],1)
|
|
end
|
|
else
|
|
if options_.opt_gsa.pprior
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_prior_' vvarvecm{iy} '_' int2str(ix) ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_prior_' vvarvecm{iy} '_' int2str(ix) ],ix,[temp_name,' observed variable ',vvarvecm_tex{iy}],['rmse_prior_' vvarvecm{iy}],1)
|
|
end
|
|
else
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_mc_' vvarvecm{iy} '_' int2str(ix)],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_mc_' vvarvecm{iy} '_' int2str(ix)],ix,[temp_name,' observed variable ',vvarvecm_tex{iy}],['rmse_mc_' vvarvecm{iy}],1)
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|
|
% now I plot by individual parameters
|
|
for ix=1:ceil(length(nsnam)/5)
|
|
hh_fig = dyn_figure(options_.nodisplay,'name',[temp_name,' estimated params and shocks ',int2str(ix)]);
|
|
for j=1+5*(ix-1):min(size(snam2,1),5*ix)
|
|
subplot(2,3,j-5*(ix-1))
|
|
h0=cumplot(x(:,nsnam(j)));
|
|
set(h0,'color',[0 0 0])
|
|
hold on,
|
|
npx=find(SP(nsnam(j),:)==0);
|
|
for i = 1:length(vvarvecm)
|
|
if any(npx==i)
|
|
h0=cumplot(x(ixx(1:nfilt0(i),i),nsnam(j))*NaN);
|
|
else
|
|
h0=cumplot(x(ixx(1:nfilt0(i),i),nsnam(j)));
|
|
if ~isoctave
|
|
hcmenu = uicontextmenu;
|
|
uimenu(hcmenu,'Label', vvarvecm{i});
|
|
set(h0,'uicontextmenu',hcmenu)
|
|
end
|
|
end
|
|
set(h0,'color',a00(i,:),'linewidth',2)
|
|
end
|
|
ydum=get(gca,'ylim');
|
|
if exist('xparam1','var')
|
|
xdum=xparam1(nsnam(j));
|
|
h1=plot([xdum xdum],ydum);
|
|
set(h1,'color',[0.85 0.85 0.85],'linewidth',2)
|
|
end
|
|
xlabel('')
|
|
if options_.TeX
|
|
title([param_names_tex{nsnam(j)}],'interpreter','latex')
|
|
else
|
|
title([param_names{nsnam(j)}],'interpreter','none')
|
|
end
|
|
end
|
|
%subplot(3,2,6)
|
|
if isoctave
|
|
legend(vertcat('base',vvarvecm),'location','eastoutside');
|
|
else
|
|
if options_.TeX
|
|
h0=legend(vertcat('base',vvarvecm_tex),'interpreter','latex');
|
|
else
|
|
h0=legend(vertcat('base',vvarvecm),'interpreter','none');
|
|
end
|
|
set(h0,'fontsize',6,'position',[0.7 0.1 0.2 0.3]);
|
|
end
|
|
if options_.opt_gsa.ppost
|
|
dyn_saveas(hh_fig,[ OutDir filesep fname_ '_rmse_post_params_' int2str(ix)],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[ OutDir filesep fname_ '_rmse_post_params_' int2str(ix)],ix,[temp_name,' estimated params and shocks ',int2str(ix)],'rmse_post_params',1)
|
|
end
|
|
else
|
|
if options_.opt_gsa.pprior
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_prior_params_' int2str(ix) ],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_prior_params_' int2str(ix) ],ix,[temp_name,' estimated params and shocks ',int2str(ix)],'rmse_prior_params',1)
|
|
end
|
|
else
|
|
dyn_saveas(hh_fig,[OutDir filesep fname_ '_rmse_mc_params_' int2str(ix)],options_.nodisplay,options_.graph_format);
|
|
if options_.TeX
|
|
create_TeX_loader(options_,[OutDir filesep fname_ '_rmse_mc_params_' int2str(ix)],ix,[temp_name,' estimated params and shocks ',int2str(ix)],'rmse_mc_params',1)
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|
|
|
|
function []=create_TeX_loader(options_,figpath,label_number,caption,label_name,scale_factor)
|
|
if nargin<6
|
|
scale_factor=1;
|
|
end
|
|
if options_.TeX && any(strcmp('eps',cellstr(options_.graph_format)))
|
|
fidTeX = fopen([figpath '.tex'],'w');
|
|
fprintf(fidTeX,'%% TeX eps-loader file generated by filt_mc_.m (Dynare).\n');
|
|
fprintf(fidTeX,['%% ' datestr(now,0) '\n\n']);
|
|
fprintf(fidTeX,'\\begin{figure}[H]\n');
|
|
fprintf(fidTeX,'\\centering \n');
|
|
fprintf(fidTeX,'\\includegraphics[width=%2.2f\\textwidth]{%s}\n',scale_factor,strrep(figpath,'\','/'));
|
|
fprintf(fidTeX,'\\caption{%s.}',caption);
|
|
fprintf(fidTeX,'\\label{Fig:%s:%u}\n',label_name,label_number);
|
|
fprintf(fidTeX,'\\end{figure}\n\n');
|
|
fprintf(fidTeX,'%% End Of TeX file. \n');
|
|
fclose(fidTeX);
|
|
end
|
|
|
|
function [pnames,pnames_tex]=get_LaTeX_parameter_names(M_,options_,estim_params_,bayestopt_)
|
|
np=size(bayestopt_.name,1);
|
|
pnames=cell(np,1);
|
|
pnames_tex=cell(np,1);
|
|
for ii=1:length(bayestopt_.name)
|
|
if options_.TeX
|
|
[param_name_temp, param_name_tex_temp]= get_the_name(ii,options_.TeX,M_,estim_params_,options_.varobs);
|
|
pnames_tex{ii,1} = param_name_tex_temp;
|
|
pnames{ii,1} = param_name_temp;
|
|
else
|
|
param_name_temp = get_the_name(ii,options_.TeX,M_,estim_params_,options_.varobs);
|
|
pnames{ii,1} = param_name_temp;
|
|
end
|
|
end
|