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GSA: cleanup and removal of globals in filt_mc_.m

new-samplers
Johannes Pfeifer 2023-11-28 16:53:43 +01:00
parent f8a0a99683
commit 152991864d
2 changed files with 73 additions and 82 deletions
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2
matlab/dynare_sensitivity.m
View File

@ -434,7 +434,7 @@ if options_gsa.rmse
end end
clear a; clear a;
% filt_mc_(OutputDirectoryName,data_info); % filt_mc_(OutputDirectoryName,data_info);
filt_mc_(OutputDirectoryName,options_gsa,dataset_,dataset_info); filt_mc_(OutputDirectoryName,options_gsa,dataset_,dataset_info,M_,oo_,options_,bayestopt_,estim_params_);
end end
options_.opt_gsa = options_gsa; options_.opt_gsa = options_gsa;
options_.prior_trunc=original_prior_trunc; options_.prior_trunc=original_prior_trunc;

153
matlab/gsa/filt_mc_.m
View File

@ -1,5 +1,21 @@
function [rmse_MC, ixx] = filt_mc_(OutDir,options_gsa_,dataset_,dataset_info) function [rmse_MC, ixx] = filt_mc_(OutDir,options_gsa_,dataset_,dataset_info,M_,oo_,options_,bayestopt_,estim_params_)
% function [rmse_MC, ixx] = filt_mc_(OutDir) % function [rmse_MC, ixx] = filt_mc_(OutDir,options_gsa_,dataset_,dataset_info,M_,oo_,options_,bayestopt_,estim_params_
% Inputs:
% - OutputDirectoryName [string] name of the output directory
% - options_gsa_ [structure] GSA options
% - dataset_ [dseries] object storing the dataset
% - dataset_info [structure] storing informations about the sample.
% - M_ [structure] Matlab's structure describing the model
% - oo_ [structure] storing the results
% - options_ [structure] Matlab's structure describing the current options
% - bayestopt_ [structure] describing the priors
% - estim_params_ [structure] characterizing parameters to be estimated
%
% Outputs:
% - rmse_MC [double] RMSE by nvar matrix of the RMSEs
% - ixx [double] RMSE by nvar matrix of sorting
% indices (descending order of RMSEs)
% inputs (from opt_gsa structure) % inputs (from opt_gsa structure)
% vvarvecm = options_gsa_.var_rmse; % vvarvecm = options_gsa_.var_rmse;
% loadSA = options_gsa_.load_rmse; % loadSA = options_gsa_.load_rmse;
@ -7,7 +23,6 @@ function [rmse_MC, ixx] = filt_mc_(OutDir,options_gsa_,dataset_,dataset_info)
% alpha = options_gsa_.alpha_rmse; % alpha = options_gsa_.alpha_rmse;
% alpha2 = options_gsa_.alpha2_rmse; % alpha2 = options_gsa_.alpha2_rmse;
% istart = options_gsa_.istart_rmse; % istart = options_gsa_.istart_rmse;
% alphaPC = 0.5;
% %
% Written by Marco Ratto % Written by Marco Ratto
% Joint Research Centre, The European Commission, % Joint Research Centre, The European Commission,
@ -31,9 +46,6 @@ function [rmse_MC, ixx] = filt_mc_(OutDir,options_gsa_,dataset_,dataset_info)
% You should have received a copy of the GNU General Public License % You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <https://www.gnu.org/licenses/>. % along with Dynare. If not, see <https://www.gnu.org/licenses/>.
global bayestopt_ estim_params_ M_ options_ oo_
% options_gsa_=options_.opt_gsa;
vvarvecm = options_gsa_.var_rmse; vvarvecm = options_gsa_.var_rmse;
if options_.TeX if options_.TeX
vvarvecm_tex = options_gsa_.var_rmse_tex; vvarvecm_tex = options_gsa_.var_rmse_tex;
@ -46,11 +58,8 @@ alpha = options_gsa_.alpha_rmse;
alpha2 = 0; alpha2 = 0;
pvalue = options_gsa_.alpha2_rmse; pvalue = options_gsa_.alpha2_rmse;
istart = max(2,options_gsa_.istart_rmse); istart = max(2,options_gsa_.istart_rmse);
alphaPC = 0.5;
fname_ = M_.fname; fname_ = M_.fname;
lgy_ = M_.endo_names;
dr_ = oo_.dr;
skipline(2) skipline(2)
disp('Starting sensitivity analysis') disp('Starting sensitivity analysis')
@ -61,12 +70,12 @@ if ~options_.nograph
a=dir([OutDir,filesep,'*.*']); a=dir([OutDir,filesep,'*.*']);
tmp1='0'; tmp1='0';
if options_.opt_gsa.ppost if options_.opt_gsa.ppost
tmp=['_rmse_post']; tmp='_rmse_post';
else else
if options_.opt_gsa.pprior if options_.opt_gsa.pprior
tmp=['_rmse_prior']; tmp='_rmse_prior';
else else
tmp=['_rmse_mc']; tmp='_rmse_mc';
end end
if options_gsa_.lik_only if options_gsa_.lik_only
tmp1 = [tmp,'_post_SA']; tmp1 = [tmp,'_post_SA'];
@ -95,7 +104,7 @@ if options_.opt_gsa.ppost
c=load([M_.dname filesep 'Output' filesep fname_,'_mean.mat'],'xparam1'); c=load([M_.dname filesep 'Output' filesep fname_,'_mean.mat'],'xparam1');
xparam1_mean=c.xparam1; xparam1_mean=c.xparam1;
clear c clear c
elseif ~isempty(options_.mode_file) && exist([M_.dname filesep 'Output' filesep fname_,'_mean.mat'])==2 elseif ~isempty(options_.mode_file) && exist([M_.dname filesep 'Output' filesep fname_,'_mean.mat'],'file')==2
c=load([M_.dname filesep 'Output' filesep fname_,'_mean.mat'],'xparam1'); c=load([M_.dname filesep 'Output' filesep fname_,'_mean.mat'],'xparam1');
xparam1_mean=c.xparam1; xparam1_mean=c.xparam1;
clear c clear c
@ -124,31 +133,11 @@ if loadSA
end end
end end
if ~loadSA if ~loadSA
if exist('xparam1','var')
M_ = set_all_parameters(xparam1,estim_params_,M_);
ys_mode=evaluate_steady_state(oo_.steady_state,[oo_.exo_steady_state; oo_.exo_det_steady_state],M_,options_,~options_.steadystate.nocheck);
end
if exist('xparam1_mean','var')
M_ = set_all_parameters(xparam1_mean,estim_params_,M_);
ys_mean=evaluate_steady_state(oo_.steady_state,[oo_.exo_steady_state; oo_.exo_det_steady_state],M_,options_,~options_.steadystate.nocheck);
end
Y = transpose(dataset_.data); Y = transpose(dataset_.data);
gend = dataset_.nobs; gend = dataset_.nobs;
data_index = dataset_info.missing.aindex; data_index = dataset_info.missing.aindex;
missing_value = dataset_info.missing.state; missing_value = dataset_info.missing.state;
for jx=1:gend
data_indx(jx,data_index{jx})=true;
end
load([DirectoryName filesep M_.fname '_data.mat']);
filfilt = dir([DirectoryName filesep M_.fname '_filter_step_ahead*.mat']); filfilt = dir([DirectoryName filesep M_.fname '_filter_step_ahead*.mat']);
temp_smooth_file_list = dir([DirectoryName filesep M_.fname '_smooth*.mat']);
jfile=0;
for j=1:length(temp_smooth_file_list)
if isempty(strfind(temp_smooth_file_list(j).name,'smoothed')),
jfile=jfile+1;
filsmooth(jfile)=temp_smooth_file_list(j);
end
end
filupdate = dir([DirectoryName filesep M_.fname '_update*.mat']); filupdate = dir([DirectoryName filesep M_.fname '_update*.mat']);
filparam = dir([DirectoryName filesep M_.fname '_param*.mat']); filparam = dir([DirectoryName filesep M_.fname '_param*.mat']);
x=[]; x=[];
@ -156,11 +145,11 @@ if ~loadSA
sto_ys=[]; sto_ys=[];
for j=1:length(filparam) for j=1:length(filparam)
if isempty(strmatch([M_.fname '_param_irf'],filparam(j).name)) if isempty(strmatch([M_.fname '_param_irf'],filparam(j).name))
load([DirectoryName filesep filparam(j).name]); temp=load([DirectoryName filesep filparam(j).name]);
x=[x; stock]; x=[x; temp.stock];
logpo2=[logpo2; stock_logpo]; logpo2=[logpo2; temp.stock_logpo];
sto_ys=[sto_ys; stock_ys]; sto_ys=[sto_ys; temp.stock_ys];
clear stock stock_logpo stock_ys; clear temp;
end end
end end
nruns=size(x,1); nruns=size(x,1);
@ -168,38 +157,41 @@ if ~loadSA
if options_.opt_gsa.ppost || (options_.opt_gsa.ppost==0 && options_.opt_gsa.lik_only==0) if options_.opt_gsa.ppost || (options_.opt_gsa.ppost==0 && options_.opt_gsa.lik_only==0)
skipline() skipline()
disp('Computing RMSE''s...') disp('Computing RMSE''s...')
jxj=NaN(length(vvarvecm),1);
js=NaN(length(vvarvecm),1);
yss=NaN(length(vvarvecm),gend,size(sto_ys,1));
for i = 1:length(vvarvecm) for i = 1:length(vvarvecm)
vj = vvarvecm{i}; vj = vvarvecm{i};
jxj(i) = strmatch(vj, lgy_(dr_.order_var), 'exact'); jxj(i) = strmatch(vj, M_.endo_names(oo_.dr.order_var), 'exact');
js(i) = strmatch(vj, lgy_, 'exact'); js(i) = strmatch(vj, M_.endo_names, 'exact');
yss(i,:,:)=repmat(sto_ys(:,js(i))',[gend,1]); yss(i,:,:)=repmat(sto_ys(:,js(i))',[gend,1]);
end end
if exist('xparam1','var') if exist('xparam1','var')
[alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = DsgeSmoother(xparam1,gend,Y,data_index,missing_value,M_,oo_,options_,bayestopt_,estim_params_); [~,~,~,ahat,~,~,aK] = DsgeSmoother(xparam1,gend,Y,data_index,missing_value,M_,oo_,options_,bayestopt_,estim_params_);
y0 = reshape( squeeze(aK(1,jxj,1:gend)),[gend length(jxj)]);% + kron(ys_mode(js),ones(1,gend))); y0 = reshape( squeeze(aK(1,jxj,1:gend)),[gend length(jxj)]);
yobs = transpose( ahat(jxj,:));% + kron(ys_mode(js),ones(1,gend))); yobs = transpose( ahat(jxj,:));
rmse_mode = sqrt(mean((yobs(istart:end,:)-y0(istart:end,:)).^2)); rmse_mode = sqrt(mean((yobs(istart:end,:)-y0(istart:end,:)).^2));
r2_mode = 1-sum((yobs(istart:end,:)-y0(istart:end,:)).^2)./sum(yobs(istart:end,:).^2); r2_mode = 1-sum((yobs(istart:end,:)-y0(istart:end,:)).^2)./sum(yobs(istart:end,:).^2);
end end
y0=-yss; y0=-yss;
nbb=0; nbb=0;
for j=1:length(filfilt) for j=1:length(filfilt)
load([DirectoryName filesep M_.fname '_filter_step_ahead',num2str(j),'.mat']); temp=load([DirectoryName filesep M_.fname '_filter_step_ahead',num2str(j),'.mat']);
nb = size(stock,4); nb = size(temp.stock,4);
y0(:,:,nbb+1:nbb+nb)=y0(:,:,nbb+1:nbb+nb)+reshape(stock(1,js,1:gend,:),[length(js) gend nb]); y0(:,:,nbb+1:nbb+nb)=y0(:,:,nbb+1:nbb+nb)+reshape(temp.stock(1,js,1:gend,:),[length(js) gend nb]);
nbb=nbb+nb; nbb=nbb+nb;
clear stock; clear temp;
end end
yobs=-yss; yobs=-yss;
nbb=0; nbb=0;
for j=1:length(filupdate) for j=1:length(filupdate)
load([DirectoryName filesep M_.fname '_update',num2str(j),'.mat']); temp=load([DirectoryName filesep M_.fname '_update',num2str(j),'.mat']);
nb = size(stock,3); nb = size(temp.stock,3);
yobs(:,:,nbb+1:nbb+nb)=yobs(:,:,nbb+1:nbb+nb)+reshape(stock(js,1:gend,:),[length(js) gend nb]); yobs(:,:,nbb+1:nbb+nb)=yobs(:,:,nbb+1:nbb+nb)+reshape(temp.stock(js,1:gend,:),[length(js) gend nb]);
nbb=nbb+nb; nbb=nbb+nb;
clear stock; clear temp;
end end
y0M=mean(y0,2);
rmse_MC=zeros(nruns,length(js)); rmse_MC=zeros(nruns,length(js));
r2_MC=zeros(nruns,length(js)); r2_MC=zeros(nruns,length(js));
for j=1:nruns for j=1:nruns
@ -207,14 +199,15 @@ if ~loadSA
r2_MC(j,:) = 1-mean((yobs(:,istart:end,j)'-y0(:,istart:end,j)').^2)./mean((yobs(:,istart:end,j)').^2); r2_MC(j,:) = 1-mean((yobs(:,istart:end,j)'-y0(:,istart:end,j)').^2)./mean((yobs(:,istart:end,j)').^2);
end end
if exist('xparam1_mean','var') if exist('xparam1_mean','var')
[alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = DsgeSmoother(xparam1_mean,gend,Y,data_index,missing_value,M_,oo_,options_,bayestopt_,estim_params_); [~,~,~,ahat,~,~,aK] = DsgeSmoother(xparam1_mean,gend,Y,data_index,missing_value,M_,oo_,options_,bayestopt_,estim_params_);
y0 = reshape( squeeze(aK(1,jxj,1:gend)),[gend length(jxj)]);% + kron(ys_mean(js),ones(1,gend))); y0 = reshape( squeeze(aK(1,jxj,1:gend)),[gend length(jxj)]);
yobs = transpose( ahat(jxj,:));% + kron(ys_mean(js),ones(1,gend))); yobs = transpose( ahat(jxj,:));
rmse_pmean = sqrt(mean((yobs(istart:end,:)-y0(istart:end,:)).^2)); rmse_pmean = sqrt(mean((yobs(istart:end,:)-y0(istart:end,:)).^2));
r2_pmean = 1-mean((yobs(istart:end,:)-y0(istart:end,:)).^2)./mean(yobs(istart:end,:).^2); r2_pmean = 1-mean((yobs(istart:end,:)-y0(istart:end,:)).^2)./mean(yobs(istart:end,:).^2);
end end
clear stock_filter; clear stock_filter;
end end
lnprior=NaN(nruns,1);
for j=1:nruns for j=1:nruns
lnprior(j,1) = priordens(x(j,:)',bayestopt_.pshape,bayestopt_.p6,bayestopt_.p7,bayestopt_.p3,bayestopt_.p4); lnprior(j,1) = priordens(x(j,:)',bayestopt_.pshape,bayestopt_.p6,bayestopt_.p7,bayestopt_.p3,bayestopt_.p4);
end end
@ -242,7 +235,7 @@ if ~loadSA
end end
end end
end end
else else % loadSA
if options_.opt_gsa.lik_only && options_.opt_gsa.ppost==0 if options_.opt_gsa.lik_only && options_.opt_gsa.ppost==0
load([OutDir,filesep,fnamtmp, '.mat'],'x','logpo2','likelihood'); load([OutDir,filesep,fnamtmp, '.mat'],'x','logpo2','likelihood');
else else
@ -252,12 +245,12 @@ else
nruns=size(x,1); nruns=size(x,1);
nfilt=floor(pfilt*nruns); nfilt=floor(pfilt*nruns);
end end
% smirnov tests % Smirnov tests
nfilt0 = nfilt*ones(length(vvarvecm), 1); nfilt0 = nfilt*ones(length(vvarvecm), 1);
logpo2=logpo2(:); logpo2=logpo2(:);
if ~options_.opt_gsa.ppost if ~options_.opt_gsa.ppost
[dum, ipost]=sort(-logpo2); [~, ipost]=sort(-logpo2);
[dum, ilik]=sort(-likelihood); [~, ilik]=sort(-likelihood);
end end
% visual scatter analysis! % visual scatter analysis!
@ -333,8 +326,8 @@ else
rmse_txt=rmse_pmean; rmse_txt=rmse_pmean;
r2_txt=r2_pmean; r2_txt=r2_pmean;
else else
if options_.opt_gsa.pprior || ~exist('rmse_pmean') if options_.opt_gsa.pprior || ~exist('rmse_pmean','var')
if exist('rmse_mode') if exist('rmse_mode','var')
rmse_txt=rmse_mode; rmse_txt=rmse_mode;
r2_txt=r2_mode; r2_txt=r2_mode;
else else
@ -346,18 +339,19 @@ else
r2_txt=r2_pmean; r2_txt=r2_pmean;
end end
end end
ixx=NaN(size(rmse_MC,1),length(vvarvecm));
for i = 1:length(vvarvecm) for i = 1:length(vvarvecm)
[dum, ixx(:,i)] = sort(rmse_MC(:,i)); [~, ixx(:,i)] = sort(rmse_MC(:,i));
end end
PP = ones(npar+nshock, length(vvarvecm)); PP = ones(npar+nshock, length(vvarvecm));
PPV = ones(length(vvarvecm), length(vvarvecm), npar+nshock); PPV = ones(length(vvarvecm), length(vvarvecm), npar+nshock);
SS = zeros(npar+nshock, length(vvarvecm)); SS = zeros(npar+nshock, length(vvarvecm));
for j = 1:npar+nshock for j = 1:npar+nshock
for i = 1:length(vvarvecm) for i = 1:length(vvarvecm)
[H, P, KSSTAT] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j), alpha); [~, P] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j), alpha);
[H1, P1, KSSTAT1] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,1); [H1] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,1);
[H2, P2, KSSTAT2] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,-1); [H2] = smirnov(x(ixx(nfilt0(i)+1:end,i),j),x(ixx(1:nfilt0(i),i),j),alpha,-1);
if H1 & H2==0 if H1==0 && H2==0
SS(j,i)=1; SS(j,i)=1;
elseif H1==0 elseif H1==0
SS(j,i)=-1; SS(j,i)=-1;
@ -369,7 +363,7 @@ else
for i = 1:length(vvarvecm) for i = 1:length(vvarvecm)
for l = 1:length(vvarvecm) for l = 1:length(vvarvecm)
if l~=i && PP(j,i)<alpha && PP(j,l)<alpha if l~=i && PP(j,i)<alpha && PP(j,l)<alpha
[H,P,KSSTAT] = smirnov(x(ixx(1:nfilt0(i),i),j),x(ixx(1:nfilt0(l),l),j), alpha); [~,P] = smirnov(x(ixx(1:nfilt0(i),i),j),x(ixx(1:nfilt0(l),l),j), alpha);
PPV(i,l,j) = P; PPV(i,l,j) = P;
elseif l==i elseif l==i
PPV(i,l,j) = PP(j,i); PPV(i,l,j) = PP(j,i);
@ -589,7 +583,7 @@ else
else else
values_length = max(ceil(max(max(log10(abs(data_mat(isfinite(data_mat))))))),1)+val_precis+1; values_length = max(ceil(max(max(log10(abs(data_mat(isfinite(data_mat))))))),1)+val_precis+1;
end end
if any(data_mat) < 0 %add one character for minus sign if any(data_mat < 0) %add one character for minus sign
values_length = values_length+1; values_length = values_length+1;
end end
headers_length = cellofchararraymaxlength(headers(2:end)); headers_length = cellofchararraymaxlength(headers(2:end));
@ -598,7 +592,6 @@ else
else else
val_width = max(headers_length, values_length)+2; val_width = max(headers_length, values_length)+2;
end end
value_format = sprintf('%%%d.%df',val_width,val_precis);
header_string_format = sprintf('%%%ds',val_width); header_string_format = sprintf('%%%ds',val_width);
if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior 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%'); 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%');
@ -610,7 +603,7 @@ else
if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior 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\%}\\']}; optional_header={[' & \multicolumn{2}{c}{best ',num2str(pfilt*100),' filtered} & \multicolumn{2}{c}{remaining 90\%}\\']};
else else
optional_header={[' & \multicolumn{2}{c}{best filtered} & \multicolumn{2}{c}{remaining}\\']}; optional_header={' & \multicolumn{2}{c}{best filtered} & \multicolumn{2}{c}{remaining}\\'};
end 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); 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 end
@ -657,7 +650,7 @@ else
else else
values_length = max(ceil(max(max(log10(abs(data_mat(isfinite(data_mat))))))),1)+val_precis+1; values_length = max(ceil(max(max(log10(abs(data_mat(isfinite(data_mat))))))),1)+val_precis+1;
end end
if any(data_mat) < 0 %add one character for minus sign if any(data_mat < 0) %add one character for minus sign
values_length = values_length+1; values_length = values_length+1;
end end
headers_length = cellofchararraymaxlength(headers(2:end)); headers_length = cellofchararraymaxlength(headers(2:end));
@ -666,7 +659,6 @@ else
else else
val_width = max(headers_length, values_length)+2; val_width = max(headers_length, values_length)+2;
end end
value_format = sprintf('%%%d.%df',val_width,val_precis);
header_string_format = sprintf('%%%ds',val_width); header_string_format = sprintf('%%%ds',val_width);
if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior
@ -679,7 +671,7 @@ else
if ~options_.opt_gsa.ppost && options_.opt_gsa.pprior if ~options_.opt_gsa.ppost && options_.opt_gsa.pprior
optional_header = {[' & \multicolumn{2}{c}{best ',num2str(pfilt*100),' filtered} & \multicolumn{2}{c}{remaining 90\%}\\']}; optional_header = {[' & \multicolumn{2}{c}{best ',num2str(pfilt*100),' filtered} & \multicolumn{2}{c}{remaining 90\%}\\']};
else else
optional_header = {[' & \multicolumn{2}{c}{best filtered} & \multicolumn{2}{c}{remaining}\\']}; optional_header = {' & \multicolumn{2}{c}{best filtered} & \multicolumn{2}{c}{remaining}\\'};
end 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); 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 end
@ -690,14 +682,13 @@ else
SP(ns,j)=ones(size(ns)); SP(ns,j)=ones(size(ns));
SS(:,j)=SS(:,j).*SP(:,j); SS(:,j)=SS(:,j).*SP(:,j);
end end
nsp=NaN(npar+nshock,1);
for j=1:npar+nshock %estim_params_.np, for j=1:npar+nshock
nsp(j)=length(find(SP(j,:))); nsp(j)=length(find(SP(j,:)));
end end
snam0=param_names(find(nsp==0)); snam0=param_names(nsp==0);
snam1=param_names(find(nsp==1)); snam1=param_names(nsp==1);
snam2=param_names(find(nsp>1)); snam2=param_names(nsp>1);
snam=param_names(find(nsp>0));
nsnam=(find(nsp>1)); nsnam=(find(nsp>1));
skipline(2) skipline(2)
disp('These parameters do not affect significantly the fit of ANY observed series:') disp('These parameters do not affect significantly the fit of ANY observed series:')
@ -767,7 +758,7 @@ else
set(h0,'color',a00(i,:),'linewidth',2) set(h0,'color',a00(i,:),'linewidth',2)
end end
ydum=get(gca,'ylim'); ydum=get(gca,'ylim');
if exist('xparam1') if exist('xparam1','var')
xdum=xparam1(ipar(j)); xdum=xparam1(ipar(j));
h1=plot([xdum xdum],ydum); h1=plot([xdum xdum],ydum);
set(h1,'color',[0.85 0.85 0.85],'linewidth',2) set(h1,'color',[0.85 0.85 0.85],'linewidth',2)
@ -824,7 +815,7 @@ else
set(h0,'color',a00(i,:),'linewidth',2) set(h0,'color',a00(i,:),'linewidth',2)
end end
ydum=get(gca,'ylim'); ydum=get(gca,'ylim');
if exist('xparam1') if exist('xparam1','var')
xdum=xparam1(nsnam(j)); xdum=xparam1(nsnam(j));
h1=plot([xdum xdum],ydum); h1=plot([xdum xdum],ydum);
set(h1,'color',[0.85 0.85 0.85],'linewidth',2) set(h1,'color',[0.85 0.85 0.85],'linewidth',2)