796 lines
34 KiB
Matlab
796 lines
34 KiB
Matlab
function redform_map(dirname,options_gsa_,M_,estim_params_,options_,bayestopt_,oo_)
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% redform_map(dirname,options_gsa_,M_,estim_params_,options_,bayestopt_,oo_)
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% Inputs:
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% - dirname [string] name of the output directory
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% - options_gsa_ [structure] GSA options_
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% - M_ [structure] describing the model
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% - estim_params_ [structure] characterizing parameters to be estimated
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% - options_ [structure] describing the options
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% - bayestopt_ [structure] describing the priors
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% - oo_ [structure] storing the results
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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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anamendo = options_gsa_.namendo;
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anamlagendo = options_gsa_.namlagendo;
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anamexo = options_gsa_.namexo;
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anamendo_tex = options_gsa_.namendo_tex;
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anamlagendo_tex = options_gsa_.namlagendo_tex;
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anamexo_tex = options_gsa_.namexo_tex;
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iload = options_gsa_.load_redform;
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pprior = options_gsa_.pprior;
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ilog = options_gsa_.logtrans_redform;
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threshold = options_gsa_.threshold_redform;
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np = estim_params_.np;
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nshock = estim_params_.nvx + estim_params_.nvn + estim_params_.ncx + estim_params_.ncn;
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pnames=cell(np,1);
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pnames_tex=cell(np,1);
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for jj=1:np
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if options_.TeX
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[param_name_temp, param_name_tex_temp]= get_the_name(nshock+jj,options_.TeX,M_,estim_params_,options_.varobs);
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pnames_tex{jj,1} = param_name_tex_temp;
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pnames{jj,1} = param_name_temp;
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else
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param_name_temp = get_the_name(nshock+jj,options_.TeX,M_,estim_params_,options_.varobs);
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pnames{jj,1} = param_name_temp;
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end
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end
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fname_ = M_.fname;
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bounds = prior_bounds(bayestopt_, options_.prior_trunc);
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if nargin==0
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dirname='';
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end
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if pprior
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load([dirname,filesep,M_.fname,'_prior'],'lpmat', 'lpmat0', 'istable','T');
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adir=[dirname filesep 'redform_prior'];
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type = 'prior';
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else
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load([dirname,filesep,M_.fname,'_mc'],'lpmat', 'lpmat0', 'istable','T');
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adir=[dirname filesep 'redform_mc'];
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type = 'mc';
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end
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options_mcf.pvalue_ks = options_gsa_.ksstat_redform;
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options_mcf.pvalue_corr = options_gsa_.alpha2_redform;
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options_mcf.alpha2 = options_gsa_.alpha2_redform;
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options_mcf.param_names = pnames;
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if options_.TeX
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options_mcf.param_names_tex = pnames_tex;
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end
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options_mcf.fname_ = M_.fname;
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options_mcf.OutputDirectoryName = adir;
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if ~exist('T','var')
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stab_map_(dirname,options_gsa_,M_,oo_,options_,bayestopt_,estim_params_);
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if pprior
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load([dirname,filesep,M_.fname,'_prior'],'T');
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else
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load([dirname,filesep,M_.fname,'_mc'],'T');
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end
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if ~exist('T','var')
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disp('The model is too large!')
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disp('Reduced form mapping stopped!')
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return
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end
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end
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if isempty(dir(adir))
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mkdir(adir)
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end
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nspred=size(T,2)-M_.exo_nbr;
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x0=lpmat(istable,:);
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if isempty(lpmat0)
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xx0=[];
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nshocks=0;
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else
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xx0=lpmat0(istable,:);
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nshocks=size(xx0,2);
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end
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[~, np]=size(x0);
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offset = length(bayestopt_.pshape)-np;
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if options_gsa_.prior_range
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pshape=5*(ones(np,1));
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pd = [NaN(np,1) NaN(np,1) bounds.lb(offset+1:end) bounds.ub(offset+1:end)];
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else
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pshape = bayestopt_.pshape(offset+1:end);
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pd = [bayestopt_.p6(offset+1:end) bayestopt_.p7(offset+1:end) bayestopt_.p3(offset+1:end) bayestopt_.p4(offset+1:end)];
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end
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options_map.param_names = pnames;
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if options_.TeX
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options_map.param_names_tex = pnames_tex;
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end
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options_map.fname_ = M_.fname;
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options_map.OutputDirectoryName = adir;
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options_map.iload = iload;
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options_map.log_trans = ilog;
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options_map.prior_range = options_gsa_.prior_range;
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options_map.pshape = pshape;
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options_map.pd = pd;
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nsok = length(find(M_.lead_lag_incidence(M_.maximum_lag,:)));
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lpmat0=[];
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js=0;
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for j = 1:length(anamendo)
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namendo = anamendo{j};
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namendo_tex = anamendo_tex{j};
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iendo = strmatch(namendo, M_.endo_names(oo_.dr.order_var), 'exact');
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ifig = 0;
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iplo = 0;
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for jx = 1:length(anamexo)
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namexo = anamexo{jx};
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namexo_tex = anamexo_tex{jx};
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iexo=strmatch(namexo, M_.exo_names, 'exact');
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skipline()
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disp(['[', namendo,' vs ',namexo,']'])
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if ~isempty(iexo)
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y0=squeeze(T(iendo,iexo+nspred,:));
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if (max(y0)-min(y0))>1.e-10
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if mod(iplo,9)==0 && isempty(threshold) && ~options_.nograph
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ifig=ifig+1;
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hh_fig = dyn_figure(options_.nodisplay,'name',['Reduced Form Mapping: ', namendo,' vs shocks ',int2str(ifig)]);
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iplo=0;
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end
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iplo=iplo+1;
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js=js+1;
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xdir0 = [adir,filesep,namendo,'_vs_', namexo];
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if ilog==0 || ~isempty(threshold)
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if isempty(threshold)
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if isempty(dir(xdir0))
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mkdir(xdir0)
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end
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atitle0=['Reduced Form Mapping (ANOVA) for ',namendo,' vs ', namexo];
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aname=[type '_' namendo '_vs_' namexo];
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atitle=[type ' Reduced Form Mapping (ANOVA): Parameter(s) driving ',namendo,' vs ',namexo];
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options_map.amap_name = aname;
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options_map.amap_title = atitle;
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options_map.figtitle = atitle0;
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options_map.title = [namendo,' vs ', namexo];
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options_map.OutputDirectoryName = xdir0;
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si(:,js) = redform_private(x0, y0, options_map, options_);
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else
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iy=find( (y0>threshold(1)) & (y0<threshold(2)));
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iyc=find( (y0<=threshold(1)) | (y0>=threshold(2)));
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xdir = [xdir0,'_threshold'];
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if isempty(dir(xdir))
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mkdir(xdir)
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end
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if ~options_.nograph
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hf=dyn_figure(options_.nodisplay,'name',['Reduced Form Mapping (Monte Carlo Filtering): ',namendo,' vs ', namexo]);
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hc = cumplot(y0);
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a=axis; delete(hc);
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x1val=max(threshold(1),a(1));
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x2val=min(threshold(2),a(2));
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hp = patch([x1val x2val x2val x1val],a([3 3 4 4]),'b');
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set(hp,'FaceColor', [0.7 0.8 1])
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hold all,
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hc = cumplot(y0);
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set(hc,'color','k','linewidth',2)
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hold off,
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if options_.TeX
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title([namendo_tex,' vs ', namexo_tex ' - threshold [' num2str(threshold(1)) ' ' num2str(threshold(2)) ']'],'interpreter','latex')
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else
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title([namendo,' vs ', namexo ' - threshold [' num2str(threshold(1)) ' ' num2str(threshold(2)) ']'],'interpreter','none')
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end
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dyn_saveas(hf,[xdir,filesep, fname_ '_' type '_' namendo,'_vs_', namexo],options_.nodisplay,options_.graph_format);
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create_TeX_loader(options_,[xdir,filesep, fname_ '_' type '_' namendo,'_vs_', namexo],['Reduced Form Mapping (Monte Carlo Filtering): ',namendo_tex,' vs ', namexo_tex],[type '_' namendo,'_vs_', namexo])
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end
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si(:,js) = NaN(np,1);
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delete([xdir, '/*threshold*.*'])
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atitle0=['Reduced Form Mapping (Monte Carlo Filtering) for ',namendo,' vs ', namexo];
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aname=[type '_' namendo '_vs_' namexo '_threshold'];
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atitle=[type ' Reduced Form Mapping (Monte Carlo Filtering): Parameter(s) driving ',namendo,' vs ',namexo];
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options_mcf.amcf_name = aname;
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options_mcf.amcf_title = atitle;
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options_mcf.beha_title = 'inside threshold';
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options_mcf.nobeha_title = 'outside threshold';
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if options_.TeX
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options_mcf.beha_title_latex = 'inside threshold';
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options_mcf.nobeha_title_latex = 'outside threshold';
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end
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options_mcf.title = atitle0;
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options_mcf.OutputDirectoryName = xdir;
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if ~isempty(iy) && ~isempty(iyc)
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fprintf(['%4.1f%% of the ',type,' support matches ',atitle0,'\n'],length(iy)/length(y0)*100)
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icheck = mcf_analysis(x0, iy, iyc, options_mcf, M_, options_, bayestopt_, estim_params_);
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lpmat=x0(iy,:);
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if nshocks
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lpmat0=xx0(iy,:);
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end
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istable=1:length(iy);
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save([xdir,filesep, fname_ '_' type '_' namendo,'_vs_', namexo '_threshold' ],'lpmat','lpmat0','istable','y0','x0','xx0','iy','iyc')
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lpmat0=[];
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if length(iy)<=10 || length(iyc)<=10
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icheck = []; % do the generic plot in any case
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end
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else
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icheck=[];
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end
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if isempty(icheck)
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if length(iy)<=10
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if isempty(iy)
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disp(['There are NO MC samples in the desired range [' num2str(threshold) ']!'])
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else
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disp(['There are TOO FEW (<=10) MC samples in the desired range [' num2str(threshold) ']!'])
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end
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elseif length(iyc)<=10
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if isempty(iyc)
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disp(['ALL MC samples are in the desired range [' num2str(threshold) ']!'])
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else
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disp(['Almost ALL MC samples are in the desired range [' num2str(threshold) ']!'])
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disp('There are TOO FEW (<=10) MC samples OUTSIDE the desired range!')
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end
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end
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atitle0=['Monte Carlo Filtering for ',namendo,' vs ', namexo];
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options_mcf.title = atitle0;
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redform_mcf(y0, x0, options_mcf, options_, M_.fname, bayestopt_.name, estim_params_);
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end
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end
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else
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atitle0=['Reduced Form Mapping (ANOVA) for log-transformed ',namendo,' vs ', namexo];
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aname=[type '_' namendo '_vs_' namexo];
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atitle=[type ' Reduced Form Mapping (ANOVA): Parameter(s) driving ',namendo,' vs ',namexo];
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options_map.amap_name = aname;
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options_map.amap_title = atitle;
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options_map.figtitle = atitle0;
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options_map.title = ['log(' namendo ' vs ' namexo ')'];
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options_map.OutputDirectoryName = xdir0;
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silog(:,js) = redform_private(x0, y0, options_map, options_);
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end
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if isempty(threshold) && ~options_.nograph
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figure(hh_fig)
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subplot(3,3,iplo),
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if ilog
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[~, iso] = sort(-silog(:,js));
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bar([silog(iso(1:min(np,10)),js)])
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logflag='log';
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else
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[~, iso] = sort(-si(:,js));
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bar(si(iso(1:min(np,10)),js))
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logflag='';
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end
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set(gca,'xticklabel',' ','fontsize',10)
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set(gca,'xlim',[0.5 10.5])
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for ip=1:min(np,10)
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if options_.TeX
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text(ip,-0.02,deblank(pnames_tex(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','latex')
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else
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text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
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end
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end
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if options_.TeX
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title([logflag,' ',namendo_tex,' vs ',namexo_tex],'interpreter','none')
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else
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title([logflag,' ',namendo,' vs ',namexo],'interpreter','none')
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end
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if iplo==9
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dyn_saveas(hh_fig,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)],options_.nodisplay,options_.graph_format);
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create_TeX_loader(options_,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)],[logflag,' ',namendo_tex,' vs ',namexo_tex],['redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)],1)
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end
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end
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else
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disp(['This entry in the shock matrix is CONSTANT = ' num2str(mean(y0),3)])
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end
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end
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end
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if iplo<9 && iplo>0 && ifig && ~options_.nograph
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dyn_saveas(hh_fig,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)],options_.nodisplay,options_.graph_format);
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create_TeX_loader(options_,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)],[logflag,' ',strrep(namendo,'_','\_'),' vs ',strrep(namexo,'_','\_')],['redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)],options_.figures.textwidth*min(iplo/3,1))
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end
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ifig=0;
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iplo=0;
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for je=1:length(anamlagendo)
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namlagendo = anamlagendo{je};
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namlagendo_tex = anamlagendo_tex{je};
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ilagendo=strmatch(namlagendo, M_.endo_names(oo_.dr.order_var(M_.nstatic+1:M_.nstatic+nsok)), 'exact');
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skipline()
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disp(['[', namendo,' vs lagged ',namlagendo,']'])
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if ~isempty(ilagendo)
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y0=squeeze(T(iendo,ilagendo,:));
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if (max(y0)-min(y0))>1.e-10
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if mod(iplo,9)==0 && isempty(threshold) && ~options_.nograph
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ifig=ifig+1;
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hh_fig = dyn_figure(options_.nodisplay,'name',['Reduced Form Mapping: ' namendo,' vs lags ',int2str(ifig)]);
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iplo=0;
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end
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iplo=iplo+1;
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js=js+1;
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xdir0 = [adir,filesep,namendo,'_vs_', namlagendo];
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if ilog==0 || ~isempty(threshold)
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if isempty(threshold)
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if isempty(dir(xdir0))
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mkdir(xdir0)
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end
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atitle0=['Reduced Form Mapping (ANOVA) for ',namendo,' vs lagged', namlagendo];
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aname=[type '_' namendo '_vs_lag_' namlagendo];
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atitle=[type ' Reduced Form Mapping (ANOVA): Parameter(s) driving ',namendo,' vs lagged',namlagendo];
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options_map.amap_name = aname;
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options_map.amap_title = atitle;
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options_map.figtitle = atitle0;
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options_map.title = [namendo,' vs ', namlagendo];
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options_map.OutputDirectoryName = xdir0;
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si(:,js) = redform_private(x0, y0, options_map, options_);
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else
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iy=find( (y0>threshold(1)) & (y0<threshold(2)));
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iyc=find( (y0<=threshold(1)) | (y0>=threshold(2)));
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xdir = [xdir0,'_threshold'];
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if isempty(dir(xdir))
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mkdir(xdir)
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end
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if ~options_.nograph
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hf=dyn_figure(options_.nodisplay,'name',['Reduced Form Mapping (Monte Carlo Filtering): ',namendo,' vs lagged ', namlagendo]);
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hc = cumplot(y0);
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a=axis; delete(hc);
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x1val=max(threshold(1),a(1));
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x2val=min(threshold(2),a(2));
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hp = patch([x1val x2val x2val x1val],a([3 3 4 4]),'b');
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set(hp,'FaceColor', [0.7 0.8 1])
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hold all,
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hc = cumplot(y0);
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set(hc,'color','k','linewidth',2)
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hold off
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if options_.TeX
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title([namendo_tex,' vs lagged ', namlagendo_tex ' - threshold [' num2str(threshold(1)) ' ' num2str(threshold(2)) ']'],'interpreter','latex')
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else
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title([namendo,' vs lagged ', namlagendo ' - threshold [' num2str(threshold(1)) ' ' num2str(threshold(2)) ']'],'interpreter','none')
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end
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dyn_saveas(hf,[xdir,filesep, fname_ '_' type '_' namendo,'_vs_', namlagendo],options_.nodisplay,options_.graph_format);
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create_TeX_loader(options_,[xdir,filesep, fname_ '_' type '_' namendo,'_vs_', namlagendo],['Reduced Form Mapping (Monte Carlo Filtering): ',namendo_tex,' vs lagged ', namlagendo_tex],[type '_' namendo,'_vs_', namlagendo],1)
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end
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delete([xdir, '/*threshold*.*'])
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atitle0=['Reduced Form Mapping (Monte Carlo Filtering) for ',namendo,' vs ', namlagendo];
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aname=[type '_' namendo '_vs_' namlagendo '_threshold'];
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atitle=[type ' Reduced Form Mapping (Monte Carlo Filtering): Parameter(s) driving ',namendo,' vs ',namlagendo];
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options_mcf.amcf_name = aname;
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options_mcf.amcf_title = atitle;
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options_mcf.beha_title = 'inside threshold';
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options_mcf.nobeha_title = 'outside threshold';
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if options_.TeX
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options_mcf.beha_title_latex = 'inside threshold';
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options_mcf.nobeha_title_latex = 'outside threshold';
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end
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options_mcf.title = atitle0;
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options_mcf.OutputDirectoryName = xdir;
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if ~isempty(iy) && ~isempty(iyc)
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fprintf(['%4.1f%% of the ',type,' support matches ',atitle0,'\n'],length(iy)/length(y0)*100)
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icheck = mcf_analysis(x0, iy, iyc, options_mcf, M_, options_, bayestopt_, estim_params_);
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lpmat=x0(iy,:);
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if nshocks
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lpmat0=xx0(iy,:);
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|
end
|
|
istable=1:length(iy);
|
|
save([xdir,filesep, fname_ '_' type '_' namendo,'_vs_', namlagendo '_threshold' ],'lpmat','lpmat0','istable','y0','x0','xx0','iy','iyc')
|
|
lpmat0=[];
|
|
if length(iy)<=10 || length(iyc)<=10
|
|
icheck = []; % do the generic plot in any case
|
|
end
|
|
else
|
|
icheck = [];
|
|
end
|
|
if isempty(icheck)
|
|
if length(iy)<=10
|
|
if isempty(iy)
|
|
disp(['There are NO MC samples in the desired range [' num2str(threshold) ']!'])
|
|
else
|
|
disp(['There are TOO FEW (<=10) MC samples in the desired range [' num2str(threshold) ']!'])
|
|
end
|
|
elseif length(iyc)<=10
|
|
if isempty(iyc)
|
|
disp(['ALL MC samples are in the desired range [' num2str(threshold) ']!'])
|
|
else
|
|
disp(['Almost ALL MC samples are in the desired range [' num2str(threshold) ']!'])
|
|
disp('There are TOO FEW (<=10) MC samples OUTSIDE the desired range!')
|
|
end
|
|
end
|
|
atitle0=['Monte Carlo Filtering for ',namendo,' vs ', namlagendo];
|
|
options_mcf.title = atitle0;
|
|
redform_mcf(y0, x0, options_mcf, options_, M_.fname, bayestopt_.name, estim_params_);
|
|
end
|
|
end
|
|
else
|
|
atitle0=['Reduced Form Mapping (ANOVA) for log-transformed ',namendo,' vs ', namlagendo];
|
|
aname=[type '_' namendo '_vs_' namlagendo];
|
|
atitle=[type ' Reduced Form Mapping (ANOVA): Parameter(s) driving ',namendo,' vs ',namlagendo];
|
|
options_map.amap_name = aname;
|
|
options_map.amap_title = atitle;
|
|
options_map.figtitle = atitle0;
|
|
options_map.title = ['log(' namendo ' vs ' namlagendo ')'];
|
|
options_map.OutputDirectoryName = xdir0;
|
|
silog(:,js) = redform_private(x0, y0, options_map, options_);
|
|
end
|
|
|
|
if isempty(threshold) && ~options_.nograph
|
|
figure(hh_fig),
|
|
subplot(3,3,iplo),
|
|
if ilog
|
|
[~, iso] = sort(-silog(:,js));
|
|
bar([silog(iso(1:min(np,10)),js)])
|
|
logflag='log';
|
|
else
|
|
[~, iso] = sort(-si(:,js));
|
|
bar(si(iso(1:min(np,10)),js))
|
|
logflag='';
|
|
end
|
|
set(gca,'xticklabel',' ','fontsize',10)
|
|
set(gca,'xlim',[0.5 10.5])
|
|
for ip=1:min(np,10)
|
|
if options_.TeX
|
|
text(ip,-0.02,deblank(pnames_tex(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','latex')
|
|
else
|
|
text(ip,-0.02,deblank(pnames(iso(ip),:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
|
|
end
|
|
end
|
|
title([logflag,' ',namendo,' vs ',namlagendo,'(-1)'],'interpreter','none')
|
|
if iplo==9
|
|
dyn_saveas(hh_fig,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)],options_.nodisplay,options_.graph_format);
|
|
create_TeX_loader(options_,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)],[logflag,' ',namendo_tex,' vs ',namlagendo_tex,'(-1)'],['redform_', namendo,'_vs_lags_',logflag,':',num2str(ifig)],1)
|
|
end
|
|
end
|
|
|
|
else
|
|
disp(['This entry in the transition matrix is CONSTANT = ' num2str(mean(y0),3)])
|
|
end
|
|
end
|
|
end
|
|
if iplo<9 && iplo>0 && ifig && ~options_.nograph
|
|
dyn_saveas(hh_fig,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)],options_.nodisplay,options_.graph_format);
|
|
create_TeX_loader(options_,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)],[logflag,' ',namendo_tex,' vs ',namlagendo_tex,'(-1)'],['redform_', namendo,'_vs_lags_',logflag,':',num2str(ifig)],options_.figures.textwidth*min(iplo/3,1));
|
|
end
|
|
end
|
|
|
|
if isempty(threshold) && ~options_.nograph
|
|
hh_fig=dyn_figure(options_.nodisplay,'name','Reduced Form GSA');
|
|
if ilog==0
|
|
myboxplot(si',[],'.',[],10)
|
|
else
|
|
myboxplot(silog',[],'.',[],10)
|
|
end
|
|
xlabel(' ')
|
|
set(gca,'xticklabel',' ','fontsize',10,'xtick',1:np)
|
|
set(gca,'xlim',[0.5 np+0.5])
|
|
set(gca,'ylim',[0 1])
|
|
set(gca,'position',[0.13 0.2 0.775 0.7])
|
|
for ip=1:np
|
|
text(ip,-0.02,deblank(pnames(ip,:)),'rotation',90,'HorizontalAlignment','right','interpreter','none')
|
|
end
|
|
if ilog==0
|
|
title('Reduced form GSA')
|
|
dyn_saveas(hh_fig,[dirname,filesep,M_.fname,'_redform_gsa'],options_.nodisplay,options_.graph_format);
|
|
create_TeX_loader(options_,[dirname,filesep,M_.fname,'_redform_gsa'],'Reduced Form GSA','redform_gsa')
|
|
else
|
|
title('Reduced form GSA - Log-transformed elements')
|
|
dyn_saveas(hh_fig,[dirname,filesep,M_.fname,'_redform_gsa_log'],options_.nodisplay,options_.graph_format);
|
|
create_TeX_loader(options_,[dirname,filesep,M_.fname,'_redform_gsa_log'],'Reduced form GSA - Log-transformed elements','redform_gsa_log')
|
|
end
|
|
end
|
|
|
|
function si = redform_private(x0, y0, options_map, options_)
|
|
np=size(x0,2);
|
|
x00=x0;
|
|
ilog = options_map.log_trans;
|
|
iload = options_map.iload;
|
|
pnames = options_map.param_names;
|
|
pd = options_map.pd;
|
|
pshape = options_map.pshape;
|
|
xdir = options_map.OutputDirectoryName;
|
|
if options_map.prior_range
|
|
for j=1:np
|
|
x0(:,j)=(x0(:,j)-pd(j,3))./(pd(j,4)-pd(j,3));
|
|
end
|
|
else
|
|
x0=priorcdf(x0,pshape, pd(:,1), pd(:,2), pd(:,3), pd(:,4));
|
|
end
|
|
|
|
if ilog
|
|
fname=[xdir filesep options_map.fname_ '_' options_map.amap_name '_log'];
|
|
else
|
|
fname=[xdir filesep options_map.fname_ '_' options_map.amap_name];
|
|
end
|
|
if iload==0
|
|
if isempty(dir(xdir))
|
|
mkdir(xdir)
|
|
end
|
|
nrun=length(y0);
|
|
nest=max(50,nrun/2);
|
|
nest=min(250,nest);
|
|
nfit=min(1000,nrun);
|
|
[~,is] = sort(y0);
|
|
istep = ceil(nrun/nest);
|
|
if istep>1
|
|
iest = is(floor(istep/2):istep:end);
|
|
nest = length(iest);
|
|
irest = is(setdiff(1:nrun,floor(istep/2):istep:nrun));
|
|
istep = ceil(length(irest)/(nfit-nest));
|
|
ifit = union(iest, irest(1:istep:end));
|
|
else
|
|
warning('the number of samples is too small for ANOVA estimation')
|
|
si=nan(np,1);
|
|
return
|
|
end
|
|
if ~ismember(irest(end),ifit)
|
|
ifit = union(ifit, irest(end));
|
|
end
|
|
nfit=length(ifit);
|
|
ipred = setdiff(1:nrun,ifit);
|
|
|
|
if ilog
|
|
[~, ~, isig, lam] = log_trans_(y0(iest));
|
|
y1 = log(y0*isig+lam);
|
|
end
|
|
if ~options_.nograph
|
|
hh_fig=dyn_figure(options_.nodisplay,'name',options_map.figtitle);
|
|
subplot(221)
|
|
if ilog
|
|
if isoctave
|
|
hist(y1,30)
|
|
else
|
|
histogram(y1,30)
|
|
end
|
|
else
|
|
if isoctave
|
|
hist(y0,30)
|
|
else
|
|
histogram(y0,30)
|
|
end
|
|
end
|
|
title(options_map.title,'interpreter','none')
|
|
subplot(222)
|
|
if ilog
|
|
hc = cumplot(y1);
|
|
else
|
|
hc = cumplot(y0);
|
|
end
|
|
set(hc,'color','k','linewidth',2)
|
|
title([options_map.title ' CDF'],'interpreter','none')
|
|
end
|
|
|
|
gsa0 = ss_anova(y0(iest), x0(iest,:), 1);
|
|
if ilog
|
|
[gsa22, gsa1, gsax] = ss_anova_log(y1(iest), x0(iest,:), isig, lam, gsa0);
|
|
end
|
|
if nfit>nest
|
|
nvr = gsa0.nvr*nest^3/nfit^3;
|
|
nvr(gsa0.stat<2) = gsa0.nvr(gsa0.stat<2)*nest^5/nfit^5;
|
|
gsa_ = ss_anova(y0(ifit), x0(ifit,:), 1, 0, 2, nvr);
|
|
if ilog
|
|
gsa0 = gsa_;
|
|
nvr1 = gsa1.nvr*nest^3/nfit^3;
|
|
nvr1(gsa1.stat<2) = gsa1.nvr(gsa1.stat<2)*nest^5/nfit^5;
|
|
nvrx = gsax.nvr*nest^3/nfit^3;
|
|
nvrx(gsax.stat<2) = gsax.nvr(gsax.stat<2)*nest^5/nfit^5;
|
|
[gsa22, gsa1, gsax] = ss_anova_log(y1(ifit), x0(ifit,:), isig, lam, gsa0, [nvr1' nvrx']);
|
|
gsa_ = gsa22;
|
|
end
|
|
else
|
|
if ilog
|
|
gsa_ = gsa22;
|
|
else
|
|
gsa_ = gsa0;
|
|
end
|
|
end
|
|
save([fname,'_map.mat'],'gsa_')
|
|
[~, iii]=sort(-gsa_.si);
|
|
gsa_.x0=x00(ifit,:);
|
|
if ~options_.nograph
|
|
hmap=gsa_sdp_plot(gsa_,[fname '_map'],pnames,iii(1:min(12,np)));
|
|
set(hmap,'name',options_map.amap_title);
|
|
end
|
|
gsa_.x0=x0(ifit,:);
|
|
if ~options_.nograph
|
|
figure(hh_fig);
|
|
subplot(223),
|
|
plot(y0(ifit),[gsa_.fit y0(ifit)],'.'),
|
|
r2 = gsa_.r2;
|
|
title(['Learning sample fit - R2=' num2str(r2,2)],'interpreter','none')
|
|
if nfit<nrun
|
|
if ilog
|
|
yf = ss_anova_fcast(x0(ipred,:), gsa1);
|
|
yf = log_trans_(yf,'',isig,lam)+ss_anova_fcast(x0(ipred,:), gsax);
|
|
else
|
|
yf = ss_anova_fcast(x0(ipred,:), gsa_);
|
|
end
|
|
yn = y0(ipred);
|
|
r2 = 1-cov(yf-yn)/cov(yn);
|
|
subplot(224),
|
|
plot(yn,[yf yn],'.'),
|
|
title(['Out-of-sample prediction - R2=' num2str(r2,2)],'interpreter','none')
|
|
end
|
|
dyn_saveas(hh_fig,fname,options_.nodisplay,options_.graph_format);
|
|
create_TeX_loader(options_,fname,['Out-of-sample prediction - R2=' num2str(r2,2)],'redform_gsa_log')
|
|
|
|
if options_.nodisplay
|
|
close(hmap);
|
|
end
|
|
end
|
|
else
|
|
load([fname,'_map.mat'],'gsa_')
|
|
if ~options_.nograph
|
|
yf = ss_anova_fcast(x0, gsa_);
|
|
hh_fig=dyn_figure(options_.nodisplay,'name',options_map.title);
|
|
plot(y0,[yf y0],'.'),
|
|
title([namy,' vs ', namx,' pred'],'interpreter','none')
|
|
dyn_saveas(hh_fig,[fname '_pred'],options_.nodisplay,options_.graph_format);
|
|
create_TeX_loader(options_,[fname '_pred'],options_map.title,[namy,' vs ', namx,' pred'])
|
|
end
|
|
end
|
|
si = gsa_.si;
|
|
|
|
return
|
|
|
|
function gsa2 = log2level_map(gsa1, isig, lam)
|
|
|
|
nest=length(gsa1.y);
|
|
np = size(gsa1.x0,2);
|
|
gsa2=gsa1;
|
|
gsa2.y = log_trans_(gsa1.y,'',isig,lam);
|
|
gsa2.fit = (exp(gsa1.fit)-lam)*isig;
|
|
gsa2.f0 = mean(gsa2.fit);
|
|
gsa2.out.SSE = sum((gsa2.fit-gsa2.y).^2);
|
|
gsa2.out.bic = gsa2.out.bic-nest*log(gsa1.out.SSE)+nest*log(gsa2.out.SSE);
|
|
gsa2.r2 = 1-cov(gsa2.fit-gsa2.y)/cov(gsa2.y);
|
|
for j=1:np
|
|
gsa2.fs(:,j) = exp(gsa1.fs(:,j)).*mean(exp(gsa1.fit-gsa1.f(:,j)))*isig-lam*isig-gsa2.f0;
|
|
gsa2.fses(:,j) = exp(gsa1.fs(:,j)+gsa1.fses(:,j)).*mean(exp(gsa1.fit-gsa1.f(:,j)))*isig-lam*isig-gsa2.f0-gsa2.fs(:,j);
|
|
gsa2.f(:,j) = exp(gsa1.f(:,j)).*mean(exp(gsa1.fit-gsa1.f(:,j)))*isig-lam*isig-gsa2.f0;
|
|
gsa2.si(j) = var(gsa2.f(:,j))/var(gsa2.y);
|
|
end
|
|
|
|
return
|
|
|
|
|
|
function [gsa22, gsa1, gsax] = ss_anova_log(y,x,isig,lam,gsa0,nvrs)
|
|
|
|
[nest, np]=size(x);
|
|
|
|
if nargin==6
|
|
gsa1 = ss_anova(y, x, 1, 0, 2, nvrs(:,1));
|
|
else
|
|
gsa1 = ss_anova(y, x, 1);
|
|
end
|
|
gsa2 = log2level_map(gsa1, isig, lam);
|
|
if nargin >=5 && ~isempty(gsa0)
|
|
nvr2=NaN(np,1);
|
|
nvr0=NaN(np,1);
|
|
for j=1:np
|
|
nvr2(j) = var(diff(gsa2.fs(:,j),2));
|
|
nvr0(j) = var(diff(gsa0.fs(:,j),2));
|
|
end
|
|
inda = find((gsa0.stat<2)&(gsa1.stat>2));
|
|
inda = inda(log10(nvr0(inda)./nvr2(inda))/2<0);
|
|
gsa1.nvr(inda)=gsa1.nvr(inda).*10.^(log10(nvr0(inda)./nvr2(inda)));
|
|
gsa1 = ss_anova(y, x, 1, 0, 2, gsa1.nvr);
|
|
gsa2 = log2level_map(gsa1, isig, lam);
|
|
end
|
|
if nargin==6
|
|
gsax = ss_anova(gsa2.y-gsa2.fit, x, 1, 0, 2, nvrs(:,2));
|
|
else
|
|
gsax = ss_anova(gsa2.y-gsa2.fit, x, 1);
|
|
end
|
|
gsa22=gsa2;
|
|
gsa22.fit = gsa2.fit+gsax.fit;
|
|
gsa22.f0 = mean(gsa22.fit);
|
|
gsa22.out.SSE = sum((gsa22.fit-gsa22.y).^2);
|
|
gsa22.out.bic = nest*log(gsa22.out.SSE/nest) + (gsax.out.df+gsa2.out.df-1)*log(nest);
|
|
gsa22.r2 = 1-sum((gsa22.fit-gsa22.y).^2)/sum((gsa22.y-mean(gsa22.y)).^2);
|
|
for j=1:np
|
|
gsa22.fs(:,j) = gsa2.fs(:,j)+gsax.fs(:,j);
|
|
gsa22.fses(:,j) = gsax.fses(:,j);
|
|
gsa22.f(:,j) = gsa2.f(:,j)+gsax.f(:,j);
|
|
gsa22.si(j) = var(gsa22.f(:,j))/var(gsa22.y);
|
|
end
|
|
|
|
return
|
|
|
|
function indmcf = redform_mcf(y0, x0, options_mcf, options_, fname, parnames, estim_params_)
|
|
|
|
hh_fig=dyn_figure(options_.nodisplay,'name',options_mcf.amcf_title);
|
|
|
|
[~, ~, ~, ~, post_deciles] = posterior_moments(y0,1,0.9);
|
|
post_deciles = [-inf; post_deciles; inf];
|
|
|
|
for jt=1:10
|
|
indy{jt}=find( (y0>post_deciles(jt)) & (y0<=post_deciles(jt+1)));
|
|
leg{jt}=[int2str(jt) '-dec'];
|
|
end
|
|
[proba] = stab_map_1(x0, indy{1}, indy{end}, [], fname, options_, parnames, estim_params_,0);
|
|
indmcf=find(proba<options_mcf.pvalue_ks);
|
|
if isempty(indmcf)
|
|
[~,jtmp] = sort(proba,1,'ascend');
|
|
indmcf = jtmp(1);
|
|
end
|
|
[~,jtmp] = sort(proba(indmcf),1,'ascend');
|
|
indmcf = indmcf(jtmp);
|
|
nbr_par = length(indmcf);
|
|
nrow=ceil(sqrt(nbr_par+1));
|
|
ncol=nrow;
|
|
if nrow*(nrow-1)>nbr_par
|
|
ncol=nrow-1;
|
|
end
|
|
|
|
cmap = colormap(jet(10));
|
|
for jx=1:nbr_par
|
|
subplot(nrow,ncol,jx)
|
|
hold off
|
|
for jt=1:10
|
|
h=cumplot(x0(indy{jt},indmcf(jx)));
|
|
set(h,'color', cmap(jt,:), 'linewidth', 2)
|
|
hold all
|
|
end
|
|
if options_.TeX
|
|
title(options_mcf.param_names_tex(indmcf(jx),:),'interpreter','latex')
|
|
else
|
|
title(options_mcf.param_names(indmcf(jx),:),'interpreter','none')
|
|
end
|
|
end
|
|
hleg = legend(leg);
|
|
aa=get(hleg,'Position');
|
|
aa(1)=1-aa(3)-0.02;
|
|
aa(2)=0.02;
|
|
set(hleg,'Position',aa);
|
|
if ~isoctave
|
|
annotation('textbox', [0.25,0.01,0.5,0.05], ...
|
|
'String', options_mcf.title, ...
|
|
'Color','black',...
|
|
'FontWeight','bold',...
|
|
'interpreter','none',...
|
|
'horizontalalignment','center');
|
|
end
|
|
|
|
dyn_saveas(hh_fig,[options_mcf.OutputDirectoryName filesep options_mcf.fname_,'_',options_mcf.amcf_name],options_.nodisplay,options_.graph_format);
|
|
create_TeX_loader(options_,[options_mcf.OutputDirectoryName filesep options_mcf.fname_,'_',options_mcf.amcf_name],strrep(options_mcf.amcf_title,'_','\_'),[options_mcf.fname_,'_',options_mcf.amcf_name])
|
|
|
|
return
|
|
|
|
function []=create_TeX_loader(options_,figpath,caption,label_name,scale_factor)
|
|
if nargin<5
|
|
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 redform_map.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,'\','/'));
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|
fprintf(fidTeX,'\\caption{%s.}',caption);
|
|
fprintf(fidTeX,'\\label{Fig:%s}\n',label_name);
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|
fprintf(fidTeX,'\\end{figure}\n\n');
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|
fprintf(fidTeX,'%% End Of TeX file. \n');
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|
fclose(fidTeX);
|
|
end
|