Revived reduced form mapping routine:
1) use new mcf_analysis.m; 2) use generic filtering when threshold does not work; 3) make log-tranformed mapping meaningful and comparable to baseline; 3) harmonize names of files saved and reduced number of directories created;time-shift
Marco Ratto
parent
0faf6e1981
commit
57e9b9fa8b
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@ -53,21 +53,31 @@ alpha2 = options_gsa_.alpha2_redform;
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alpha2=0;
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pvalue_ks = options_gsa_.ksstat_redform;
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pvalue_corr = options_gsa_.alpha2_redform;
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pnames = M_.param_names(estim_params_.param_vals(:,1),:);
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fname_ = M_.fname;
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bounds = prior_bounds(bayestopt_,options_);
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pnames = M_.param_names(estim_params_.param_vals(:,1),:);
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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_stab'];
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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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options_mcf.fname_ = M_.fname;
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options_mcf.OutputDirectoryName = adir;
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if ~exist('T')
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stab_map_(dirname,options_gsa_);
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if pprior
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@ -106,6 +116,15 @@ else
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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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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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lpmat=[];
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lpmat0=[];
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@ -119,7 +138,7 @@ for j=1:size(anamendo,1)
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namexo=deblank(anamexo(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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disp(['[', namendo,' vs ',namexo,']'])
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if ~isempty(iexo),
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@ -128,7 +147,7 @@ for j=1:size(anamendo,1)
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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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hfig = dyn_figure(options_,'name',['Reduced Form Mapping: ', namendo,' vs. shocks ',int2str(ifig)]);
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hfig = dyn_figure(options_,'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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@ -139,7 +158,15 @@ for j=1:size(anamendo,1)
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if isempty(dir(xdir0))
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mkdir(xdir0)
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end
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si(:,js) = redform_private(x0, y0, pshape, pd, iload, pnames, namendo, namexo, xdir0, options_gsa_);
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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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@ -148,41 +175,65 @@ for j=1:size(anamendo,1)
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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_,'name',['Reduced Form Mapping: ',namendo,' vs. ', namexo]); hist(y0,30), title([namendo,' vs. ', namexo],'interpreter','none')
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dyn_saveas(hf,[xdir,filesep, namendo,'_vs_', namexo],options_);
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hf=dyn_figure(options_,'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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% hist(mat_moment{ij}),
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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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title([namendo,' vs ', namexo ' - threshold [' num2str(threshold(1)) ' ' num2str(threshold(2)) ']'],'interpreter','none')
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dyn_saveas(hf,[xdir,filesep, fname_ '_' type '_' namendo,'_vs_', namexo],options_);
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end
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% if ~isempty(iy),
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% si(:,js) = redform_private(x0(iy,:), y0(iy), pshape, pd, iload, pnames, namendo, namexo, xdir, options_gsa_);
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% else
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si(:,js) = NaN(np,1);
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% end
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if length(iy)>size(x0,2) && length(iyc)>size(x0,2)
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delete([xdir, '/*threshold*.*'])
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[proba, dproba] = stab_map_1(x0, iy, iyc, 'threshold',0);
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% indsmirnov = find(dproba>ksstat);
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indsmirnov = find(proba<pvalue_ks);
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for jp=1:length(indsmirnov),
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disp([M_.param_names(estim_params_.param_vals(indsmirnov(jp),1),:),' d-stat = ', num2str(dproba(indsmirnov(jp)),'%1.3f'),' p-value = ', num2str(proba(indsmirnov(jp)),'%1.3f')])
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end
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skipline()
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stab_map_1(x0, iy, iyc, 'threshold',pvalue_ks,indsmirnov,xdir,[],['Reduced Form Mapping (Threshold) for ', namendo,' vs. lagged ', namexo]);
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stab_map_2(x0(iy,:),alpha2,pvalue_corr,'inside_threshold',xdir,[],['Reduced Form Mapping (Inside Threshold)for ', namendo,' vs. lagged ', namexo])
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stab_map_2(x0(iyc,:),alpha2,pvalue_corr,'outside_threshold',xdir,[],['Reduced Form Mapping (Outside Threshold) for ', namendo,' vs. lagged ', namexo])
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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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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, options_);
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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,'threshold.mat'],'lpmat','lpmat0','istable','y0','x0','xx0','iy','iyc')
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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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lpmat=[]; lpmat0=[]; istable=[];
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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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atitle0=['Monte Carlo Filtering for ',namendo,' vs ', namexo];
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options_mcf.title = atitle0;
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indmcf = redform_mcf(y0, x0, options_mcf, options_);
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end
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end
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else
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[yy, xdir] = log_trans_(y0,xdir0);
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if isempty(dir(xdir))
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mkdir(xdir)
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end
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silog(:,js) = redform_private(x0, yy, pshape, pd, iload, pnames, namendo, namexo, xdir, options_gsa_);
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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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@ -203,7 +254,7 @@ for j=1:size(anamendo,1)
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for ip=1:min(np,10),
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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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title([logflag,' ',namendo,' vs. ',namexo],'interpreter','none')
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title([logflag,' ',namendo,' vs ',namexo],'interpreter','none')
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if iplo==9,
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dyn_saveas(hfig,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_shocks_',logflag,num2str(ifig)],options_);
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end
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@ -221,7 +272,7 @@ for j=1:size(anamendo,1)
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namlagendo=deblank(anamlagendo(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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disp(['[', namendo,' vs lagged ',namlagendo,']'])
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if ~isempty(ilagendo),
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%y0=squeeze(T(iendo,ilagendo,istable));
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@ -229,7 +280,7 @@ for j=1:size(anamendo,1)
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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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hfig = dyn_figure(options_,'name',['Reduced Form Mapping: ' namendo,' vs. lags ',int2str(ifig)]);
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hfig = dyn_figure(options_,'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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@ -240,7 +291,15 @@ for j=1:size(anamendo,1)
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if isempty(dir(xdir0))
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mkdir(xdir0)
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end
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si(:,js) = redform_private(x0, y0, pshape, pd, iload, pnames, namendo, namlagendo, xdir0, options_gsa_);
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atitle0=['Reduced Form Mapping (ANOVA) for ',namendo,' vs ', namlagendo];
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aname=[type '_' namendo '_vs_' namlagendo];
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atitle=[type ' Reduced Form Mapping (ANOVA): Parameter(s) driving ',namendo,' vs ',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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@ -248,41 +307,67 @@ for j=1:size(anamendo,1)
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if isempty(dir(xdir))
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mkdir(xdir)
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end
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% if ~isempty(iy)
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% si(:,js) = redform_private(x0(iy,:), y0(iy), pshape, pd, iload, pnames, namendo, namlagendo, xdir, options_gsa_);
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% end
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if ~options_.nograph,
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hf=dyn_figure(options_,'name',['Reduced Form Mapping: ',namendo,' vs. lagged ', namlagendo]); hist(y0,30), title([namendo,' vs. lagged ', namlagendo],'interpreter','none')
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dyn_saveas(hf,[xdir,filesep, namendo,'_vs_', namlagendo],options_);
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hf=dyn_figure(options_,'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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% hist(mat_moment{ij}),
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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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title([namendo,' vs lagged ', namlagendo ' - threshold [' num2str(threshold(1)) ' ' num2str(threshold(2)) ']'],'interpreter','none')
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dyn_saveas(hf,[xdir,filesep, fname_ '_' type '_' namendo,'_vs_', namlagendo],options_);
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end
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if length(iy)>size(x0,2) && length(iyc)>size(x0,2),
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delete([xdir, '/*threshold*.*'])
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[proba, dproba] = stab_map_1(x0, iy, iyc, 'threshold',0);
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% indsmirnov = find(dproba>ksstat);
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indsmirnov = find(proba<pvalue_ks);
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for jp=1:length(indsmirnov),
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disp([M_.param_names(estim_params_.param_vals(indsmirnov(jp),1),:),' d-stat = ', num2str(dproba(indsmirnov(jp)),'%1.3f'),' p-value = ', num2str(proba(indsmirnov(jp)),'%1.3f')])
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end
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skipline()
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stab_map_1(x0, iy, iyc, 'threshold',pvalue_ks,indsmirnov,xdir,[],['Reduced Form Mapping (Threshold) for ', namendo,' vs. lagged ', namlagendo]);
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stab_map_2(x0(iy,:),alpha2,pvalue_corr,'inside_threshold',xdir,[],['Reduced Form Mapping (Inside Threshold) for ', namendo,' vs. lagged ', namlagendo])
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stab_map_2(x0(iyc,:),alpha2,pvalue_corr,'outside_threshold',xdir,[],['Reduced Form Mapping (Outside Threshold) for ', namendo,' vs. lagged ', namlagendo])
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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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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, options_);
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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,'threshold.mat'],'lpmat','lpmat0','istable','y0','x0','xx0','iy','iyc')
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save([xdir,filesep, fname_ '_' type '_' namendo,'_vs_', namlagendo '_threshold' ],'lpmat','lpmat0','istable','y0','x0','xx0','iy','iyc')
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lpmat=[]; lpmat0=[]; istable=[];
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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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atitle0=['Monte Carlo Filtering for ',namendo,' vs ', namlagendo];
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options_mcf.title = atitle0;
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indmcf = redform_mcf(y0, x0, options_mcf, options_);
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end
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end
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else
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[yy, xdir] = log_trans_(y0,xdir0);
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if isempty(dir(xdir))
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mkdir(xdir)
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end
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silog(:,js) = redform_private(x0, yy, pshape, pd, iload, pnames, namendo, namlagendo, xdir, options_gsa_);
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atitle0=['Reduced Form Mapping (ANOVA) for log-transformed ',namendo,' vs ', namlagendo];
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aname=[type '_' namendo '_vs_' namlagendo];
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atitle=[type ' Reduced Form Mapping (ANOVA): Parameter(s) driving ',namendo,' vs ',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 = ['log(' namendo ' vs ' namlagendo ')'];
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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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@ -303,7 +388,7 @@ for j=1:size(anamendo,1)
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for ip=1:min(np,10),
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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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title([logflag,' ',namendo,' vs. ',namlagendo,'(-1)'],'interpreter','none')
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title([logflag,' ',namendo,' vs ',namlagendo,'(-1)'],'interpreter','none')
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if iplo==9,
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dyn_saveas(hfig,[dirname,filesep,M_.fname,'_redform_', namendo,'_vs_lags_',logflag,num2str(ifig)],options_);
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end
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@ -351,13 +436,17 @@ if isempty(threshold) && ~options_.nograph,
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end
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end
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function si = redform_private(x0, y0, pshape, pd, iload, pnames, namy, namx, xdir, opt_gsa)
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global bayestopt_ options_
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function si = redform_private(x0, y0, options_map, options_)
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% opt_gsa=options_.opt_gsa;
|
||||
np=size(x0,2);
|
||||
x00=x0;
|
||||
if opt_gsa.prior_range,
|
||||
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
|
||||
|
|
@ -365,61 +454,286 @@ else
|
|||
x0=priorcdf(x0,pshape, pd(:,1), pd(:,2), pd(:,3), pd(:,4));
|
||||
end
|
||||
|
||||
fname=[xdir,'/map'];
|
||||
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
|
||||
if ~options_.nograph,
|
||||
hfig=dyn_figure(options_,'name',['Reduced Form Mapping: ', namy,' vs. ', namx]); hist(y0,30), title([namy,' vs. ', namx],'interpreter','none')
|
||||
dyn_saveas(hfig,[xdir,filesep, namy,'_vs_', namx],options_);
|
||||
end
|
||||
% gsa_ = gsa_sdp_dyn(y0, x0, -2, [],[],[],1,fname, pnames);
|
||||
nrun=length(y0);
|
||||
nest=min(250,nrun);
|
||||
nfit=min(1000,nrun);
|
||||
% dotheplots = (nfit<=nest);
|
||||
gsa_ = gsa_sdp(y0(1:nest), x0(1:nest,:), 2, [],[-1 -1 -1 -1 -1 0],[],0,[fname,'_est'], pnames);
|
||||
if nfit>nest,
|
||||
gsa_ = gsa_sdp(y0(1:nfit), x0(1:nfit,:), -2, gsa_.nvr*nest^3/nfit^3,[-1 -1 -1 -1 -1 0],[],0,fname, pnames);
|
||||
% gsa_ = gsa_sdp(y0(1:nest), x0(1:nest,:), 2, [],[-1 -1 -1 -1 -1 0],[],0,[fname,'_est'], pnames);
|
||||
[ys,is] = sort(y0);
|
||||
istep = ceil(nrun/nest);
|
||||
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));
|
||||
if ~ismember(irest(end),ifit),
|
||||
ifit = union(ifit, irest(end));
|
||||
end
|
||||
nfit=length(ifit);
|
||||
% ifit = union(iest, irest(randperm(nrun-nest,nfit-nest)));
|
||||
% ifit = iest;
|
||||
% nfit=nest;
|
||||
ipred = setdiff([1:nrun],ifit);
|
||||
|
||||
if ilog,
|
||||
[y1, tmp, isig, lam] = log_trans_(y0(iest));
|
||||
y1 = log(y0*isig+lam);
|
||||
end
|
||||
save([fname,'.mat'],'gsa_')
|
||||
[sidum, iii]=sort(-gsa_.si);
|
||||
gsa_.x0=x00(1:nfit,:);
|
||||
if ~options_.nograph,
|
||||
hfig=gsa_sdp_plot(gsa_,fname,pnames,iii(1:min(12,np)));
|
||||
if options_.nodisplay
|
||||
close(hfig);
|
||||
hfig=dyn_figure(options_,'name',options_map.figtitle);
|
||||
subplot(221)
|
||||
if ilog,
|
||||
hist(y1,30),
|
||||
else
|
||||
hist(y0,30),
|
||||
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
|
||||
gsa_.x0=x0(1:nfit,:);
|
||||
|
||||
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 (gsa1.out.bic-gsa0.out.bic) < 10,
|
||||
% y00=y0;
|
||||
% gsa00=gsa0;
|
||||
% gsa0=gsa1;
|
||||
% y0=y1;
|
||||
% ilog=1;
|
||||
% end
|
||||
if nfit>nest,
|
||||
% gsa_ = gsa_sdp(y0(1:nfit), x0(1:nfit,:), -2, gsa_.nvr*nest^3/nfit^3,[-1 -1 -1 -1 -1 0],[],0,fname, pnames);
|
||||
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']);
|
||||
% gsa1 = ss_anova(y1(ifit), x0(ifit,:), 1, 0, 2, nvr);
|
||||
% gsa2=gsa1;
|
||||
% gsa2.y = gsa0.y;
|
||||
% 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.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
|
||||
% nvr = gsax.nvr*nest^3/nfit^3;
|
||||
% nvr(gsax.stat<2) = gsax.nvr(gsax.stat<2)*nest^5/nfit^5;
|
||||
% gsax = ss_anova([gsa2.y-gsa2.fit], x0(ifit,:), 1, 0, 2, nvr);
|
||||
% 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.f(:,j) = gsa2.f(:,j)+gsax.f(:,j);
|
||||
% gsa22.si(j) = var(gsa22.f(:,j))/var(gsa22.y);
|
||||
% end
|
||||
gsa_ = gsa22;
|
||||
end
|
||||
else
|
||||
if ilog
|
||||
gsa_ = gsa22;
|
||||
else
|
||||
gsa_ = gsa0;
|
||||
end
|
||||
end
|
||||
save([fname,'_map.mat'],'gsa_')
|
||||
[sidum, 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,:);
|
||||
% copyfile([fname,'_est.mat'],[fname,'.mat'])
|
||||
if ~options_.nograph,
|
||||
hfig=dyn_figure(options_,'name',['Reduced Form Mapping: ' namy,'_vs_', namx,'_fit']);
|
||||
plot(y0(1:nfit),[gsa_.fit y0(1:nfit)],'.'),
|
||||
title([namy,' vs. ', namx,' fit'],'interpreter','none')
|
||||
dyn_saveas(hfig,[xdir,filesep, namy,'_vs_', namx,'_fit'],options_);
|
||||
figure(hfig);
|
||||
subplot(223),
|
||||
plot(y0(ifit),[gsa_.fit y0(ifit)],'.'),
|
||||
r2 = gsa_.r2;
|
||||
% if ilog,
|
||||
% plot(y00(ifit),[log_trans_(gsa_.fit,'',isig,lam) y00(ifit)],'.'),
|
||||
% r2 = 1 - cov(log_trans_(gsa_.fit,'',isig,lam)-y00(ifit))/cov(y00(ifit));
|
||||
% else
|
||||
% plot(y0(ifit),[gsa_.fit y0(ifit)],'.'),
|
||||
% r2 = gsa_.r2;
|
||||
% end
|
||||
title(['Learning sample fit - R2=' num2str(r2,2)],'interpreter','none')
|
||||
if nfit<nrun,
|
||||
npred=[nfit+1:nrun];
|
||||
yf = ss_anova_fcast(x0(npred,:), gsa_);
|
||||
hfig=dyn_figure(options_,'name',['Reduced Form Mapping: ' namy,'_vs_', namx,'_pred']);
|
||||
plot(y0(npred),[yf y0(npred)],'.'),
|
||||
title([namy,' vs. ', namx,' pred'],'interpreter','none')
|
||||
dyn_saveas(hfig,[xdir,filesep, namy,'_vs_', namx,'_pred'],options_);
|
||||
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(hfig,fname,options_);
|
||||
|
||||
if options_.nodisplay
|
||||
close(hmap);
|
||||
end
|
||||
end
|
||||
else
|
||||
% gsa_ = gsa_sdp_dyn(y0, x0, 0, [],[],[],0,fname, pnames);
|
||||
gsa_ = gsa_sdp(y0, x0, 0, [],[],[],0,fname, pnames);
|
||||
% gsa_ = gsa_sdp(y0, x0, 0, [],[],[],0,fname, pnames);
|
||||
load([fname,'_map.mat'],'gsa_')
|
||||
if ~options_.nograph,
|
||||
yf = ss_anova_fcast(x0, gsa_);
|
||||
hfig=dyn_figure(options_,['Reduced Form Mapping: ' namy,'_vs_', namx,'_pred']);
|
||||
hfig=dyn_figure(options_,'name',options_map.title);
|
||||
plot(y0,[yf y0],'.'),
|
||||
title([namy,' vs. ', namx,' pred'],'interpreter','none')
|
||||
dyn_saveas(hfig,[xdir,filesep, namy,'_vs_', namx,'_pred'],options_);
|
||||
title([namy,' vs ', namx,' pred'],'interpreter','none')
|
||||
dyn_saveas(hfig,[fname '_pred'],options_);
|
||||
end
|
||||
end
|
||||
% si = gsa_.multivariate.si;
|
||||
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),
|
||||
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_)
|
||||
|
||||
hfig=dyn_figure(options_,'name',options_mcf.amcf_title);
|
||||
|
||||
[post_mean, post_median, post_var, hpd_interval, post_deciles, ...
|
||||
density] = 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, dproba] = stab_map_1(x0, indy{1}, indy{end}, [],0);
|
||||
indmcf=find(proba<options_mcf.pvalue_ks);
|
||||
[tmp,jtmp] = sort(proba(indmcf),2,'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
|
||||
title(options_mcf.param_names(indmcf(jx),:),'interpreter','none')
|
||||
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(hfig,[options_mcf.OutputDirectoryName filesep options_mcf.fname_,'_',options_mcf.amcf_name],options_);
|
||||
|
||||
return
|
||||
|
|
|
|||
Loading…
Reference in New Issue