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Identification is made compatible with octave.

time-shift
Marco Ratto 2011-10-27 13:09:26 +02:00
parent d806fdd617
commit 3367014970
4 changed files with 77 additions and 44 deletions
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15
matlab/dynare_identification.m
View File

@ -267,7 +267,7 @@ if iload <=0,
if SampleSize > 1,
disp(' ')
disp('Monte Carlo Testing')
h = waitbar(0,'Monte Carlo identification checks ...');
h = dyn_waitbar(0,'Monte Carlo identification checks ...');
iteration = 0;
loop_indx = 0;
file_index = 0;
@ -364,7 +364,11 @@ if iload <=0,
end
if SampleSize > 1,
waitbar(iteration/SampleSize,h,['MC identification checks ',int2str(iteration),'/',int2str(SampleSize)])
% if exist('OCTAVE_VERSION') || options_.console_mode,
% console_waitbar(0,iteration/SampleSize);
% else
dyn_waitbar(iteration/SampleSize,h,['MC identification checks ',int2str(iteration),'/',int2str(SampleSize)])
% end
end
end
@ -372,7 +376,12 @@ if iload <=0,
if SampleSize > 1,
close(h),
if exist('OCTAVE_VERSION') || options_.console_mode,
fprintf('\n');
diary on;
else
close(h),
end
normTAU=std(TAU')';
normLRE=std(LRE')';
normGAM=std(GAM')';

8
matlab/ident_bruteforce.m
View File

@ -25,7 +25,7 @@ function [pars, cosnJ] = ident_bruteforce(J,n,TeX, pnames_TeX)
%
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licen
global M_
global M_ options_
OutputDirectoryName = CheckPath('Identification');
@ -41,7 +41,7 @@ end
cosnJ=zeros(k,n);
pars{k,n}=[];
for ll = 1:n,
h = waitbar(0,['Brute force collinearity for ' int2str(ll) ' parameters.']);
h = dyn_waitbar(0,['Brute force collinearity for ' int2str(ll) ' parameters.']);
for ii = 1:k
tmp = find([1:k]~=ii);
tmp2 = nchoosek(tmp,ll);
@ -61,9 +61,9 @@ for ll = 1:n,
else
pars{ii,ll} = NaN(1,ll);
end
waitbar(ii/k,h)
dyn_waitbar(ii/k,h)
end
close(h),
dyn_waitbar_close(h);
if TeX
filename = [OutputDirectoryName '/' M_.fname '_collinearity_patterns' int2str(ll) '.TeX'];
fidTeX = fopen(filename,'w');

92
matlab/plot_identification.m
View File

@ -39,7 +39,7 @@ function plot_identification(params,idemoments,idehess,idemodel, idelre, advance
global M_ options_
if nargin<10 || isempty(save_figure),
save_figure=0;
save_figure=1;
end
[SampleSize, nparam]=size(params);
@ -88,9 +88,11 @@ if SampleSize == 1,
else
title('Sensitivity component with moments Information matrix (log-scale)')
end
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_ident_strength_',tittxt1])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_strength_' tittxt1]);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_strength_' tittxt1]);
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_strength_' tittxt1 '.eps']);
if ~exist('OCTAVE_VERSION'),
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_ident_strength_',tittxt1])
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_strength_' tittxt1]);
end
if advanced,
disp(' ')
@ -112,14 +114,14 @@ if SampleSize == 1,
for ip=1:nparam,
text(ip,dy(1),name{is(ip)},'rotation',90,'HorizontalAlignment','right','interpreter','none')
end
if advanced,
legend('Moments','Model','LRE model','Location','Best')
end
title('Sensitivity bars using derivatives (log-scale)')
if save_figure
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_sensitivity_',tittxt1])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_sensitivity_' tittxt1]);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_sensitivity_' tittxt1]);
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_sensitivity_' tittxt1 '.eps']);
if ~exist('OCTAVE_VERSION'),
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_sensitivity_',tittxt1])
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_sensitivity_' tittxt1]);
end
close(gcf);
end
% identificaton patterns
@ -159,12 +161,14 @@ if SampleSize == 1,
end
set(gca,'xgrid','on')
set(gca,'ygrid','on')
xlabel([tittxt,' - Collinearity patterns with ', int2str(j) ,' parameter(s)'])
xlabel([tittxt,' - Collinearity patterns with ', int2str(j) ,' parameter(s)'],'interpreter','none')
if save_figure
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_ident_collinearity_', tittxt1, '_', int2str(j)])
eval(['print -depsc ' IdentifDirectoryName '/' M_.fname '_ident_collinearity_' tittxt1 '_' int2str(j)]);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_collinearity_' tittxt1 '_' int2str(j)]);
if options_.nograph, close(gcf); end
eval(['print -depsc ' IdentifDirectoryName '/' M_.fname '_ident_collinearity_' tittxt1 '_' int2str(j) '.eps']);
if ~exist('OCTAVE_VERSION'),
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_ident_collinearity_', tittxt1, '_', int2str(j)])
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_collinearity_' tittxt1 '_' int2str(j)]);
end
close(gcf);
end
end
disp('')
@ -213,14 +217,20 @@ if SampleSize == 1,
end
if save_figure,
figure(f1);
saveas(f1,[IdentifDirectoryName,'/',M_.fname,'_ident_pattern_',tittxt1,'_1'])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_1']);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_1']);
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_1.eps']);
if ~exist('OCTAVE_VERSION'),
saveas(f1,[IdentifDirectoryName,'/',M_.fname,'_ident_pattern_',tittxt1,'_1'])
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_1']);
end
close(f1);
if nparam>4,
figure(f2),
saveas(f2,[IdentifDirectoryName,'/',M_.fname,'_ident_pattern_',tittxt1,'_2'])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_2']);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_2']);
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_2.eps']);
if ~exist('OCTAVE_VERSION'),
saveas(f2,[IdentifDirectoryName,'/',M_.fname,'_ident_pattern_',tittxt1,'_2'])
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_pattern_' tittxt1 '_2']);
end
close(f2);
end
end
end
@ -252,14 +262,16 @@ else
legend('Moments','Model','LRE model','Location','Best')
end
title('MC mean of sensitivity measures')
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_MC_sensitivity'])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_MC_sensitivity']);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_MC_sensitivity']);
if options_.nograph, close(gcf); end
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_MC_sensitivity.eps']);
if ~exist('OCTAVE_VERSION'),
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_MC_sensitivity'])
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_MC_sensitivity']);
end
close(gcf);
if advanced,
disp(' ')
disp('Press ENTER to display advanced diagnostics'), pause(5),
options_.nograph=1;
% options_.nograph=1;
figure('Name','MC Condition Number'),
subplot(221)
hist(log10(idemodel.cond))
@ -270,10 +282,12 @@ else
subplot(223)
hist(log10(idelre.cond))
title('log10 of Condition number in the LRE model')
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_ident_COND'])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_COND']);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_COND']);
if options_.nograph, close(gcf); end
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_ident_COND.eps']);
if ~exist('OCTAVE_VERSION'),
saveas(gcf,[IdentifDirectoryName,'/',M_.fname,'_ident_COND'])
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_ident_COND']);
end
close(gcf);
ncut=floor(SampleSize/10*9);
[dum,is]=sort(idelre.cond);
[proba, dproba] = stab_map_1(params, is(1:ncut), is(ncut+1:end), 'MC_HighestCondNumberLRE', 1, [], IdentifDirectoryName, 0.1);
@ -334,14 +348,20 @@ else
end
if save_figure,
figure(f1);
saveas(f1,[IdentifDirectoryName,'/',M_.fname,'_MC_dent_pattern_1'])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_MC_ident_pattern_1']);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_MC_ident_pattern_1']);
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_MC_ident_pattern_1.eps']);
if ~exist('OCTAVE_VERSION'),
saveas(f1,[IdentifDirectoryName,'/',M_.fname,'_MC_dent_pattern_1'])
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_MC_ident_pattern_1']);
end
close(f1);
if nparam>4,
figure(f2),
saveas(f2,[IdentifDirectoryName,'/',M_.fname,'_MC_ident_pattern_2'])
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_MC_ident_pattern_2']);
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_MC_ident_pattern_2']);
eval(['print -depsc2 ' IdentifDirectoryName '/' M_.fname '_MC_ident_pattern_2.eps']);
if ~exist('OCTAVE_VERSION'),
saveas(f2,[IdentifDirectoryName,'/',M_.fname,'_MC_ident_pattern_2'])
eval(['print -dpdf ' IdentifDirectoryName '/' M_.fname '_MC_ident_pattern_2']);
end
close(f2);
end
end
end

6
matlab/vnorm.m
View File

@ -67,7 +67,11 @@ if nargin>1
end
end
if isempty(dim)
idx = find(size(A)~=1);
dim = idx(1);
end
if isempty(ntype)
y = sqrt(sum( abs(A).^2 , dim) );
elseif ntype==1