arfit.m 26.41 KiB
function varargout=arfit(varargin)
% ARFIT AR parameter estimation via Yule-Walker method.
% ARFIT(X,P) opens a GUI for AR coefficients
% estimation for the vector X using the Yule-Walker
% method. The coefficients and order selection criterias
% for all orders until the maximal order P will be
% solved. The coefficients are solved by the Levinson-
% Durbin algorithmus. The criteria are normalized in
% order to show them in the same plot.
%
% A=ARFIT(X,P) returns the vector A of length (P+1) of
% the AR coefficients and the noise level for the
% corresponding AR model of the model order P. The GUI
% is suppressed.
%
% [A Y]=ARFIT(X,P) returns the vector Y of a realization
% of the resulting AR model. The GUI is suppressed.
%
% Example: x = rand(3,1);
% a = [.8 .3 -.25 .9]';
% for i = 4:1000,
% x(i) = sum(a(1:3) .* x(i-1:-1:i-3)) + a(end) * randn;
% end
% arfit(x,10)
% Copyright (c) 2008-2009
% Norbert Marwan, Potsdam Institute for Climate Impact Research, Germany
% http://www.pik-potsdam.de
%
% Copyright (c) 2002-2008
% Norbert Marwan, Potsdam University, Germany
% http://www.agnld.uni-potsdam.de
%
% $Date$
% $Revision$
%
% $Log$
% Revision 2.7 2007/12/20 16:26:05 marwan
% changed gpl splash behaviour
%
% Revision 2.6 2007/05/24 12:30:55 marwan
% definitions of criteria checked and corrected
%
% Revision 2.5 2006/02/14 11:45:49 marwan
% *** empty log message ***
%
% Revision 2.4 2005/03/16 11:19:02 marwan
% help text modified
%
% Revision 2.3 2004/11/10 07:05:48 marwan
% initial import
%
%
% This program is part of the new generation XXII series.
%
% This program is free software; you can redistribute it and/or
% modify it under the terms of the GNU General Public License
% as published by the Free Software Foundation; either version 2
% of the License, or any later version.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% programme properties
global props
init_properties
crit=[];
for i=1:6
props.criteria_line(i).Marker='none';
props.criteria_line(i).LineWidth=props.line.LineWidth;
props.criteria_line(i).LineStyle=props.line.LineStyle;end
props.criteria_line(6).LineStyle=':';
props.criteria_line(1).Color=[ 0 0 0];
props.criteria_line(2).Color=[.8 0 0];
props.criteria_line(3).Color=[ 0 0 .8];
props.criteria_line(4).Color=[ 0 .6 0];
props.criteria_line(5).Color=[.47 .4 .1];
props.criteria_line(6).Color=[.6 .6 .6];
if ~isempty(findobj('Tag','helpdlgbox')), delete(findobj('tag','helpdlgbox')), end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% splash the GPL
splash_gpl('crp');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% check and read the input
error(nargchk(1,3,nargin));
if nargout>2, error('Too many output arguments.'), end
%%%%%% read the command line
if isnumeric(varargin{1})==1
i_double=find(cellfun('isclass',varargin,'double'));
i_char=find(cellfun('isclass',varargin,'char'));
%%%%%% check whether to create the gui
nogui=0;
check_gui={'gui','nog','sil'}; % gui, nogui, silent
if ~isempty(i_char)
temp_gui=0;
for i=1:length(i_char),
temp_gui=temp_gui+strcmpi(varargin{i_char(i)}(1:3),check_gui');
end
nogui=min(find(temp_gui))-1;
else
nogui=0;
end
if nargout>0, nogui=1; end
%%%%%% get the numeric input variables
if ~isempty(i_double)
for i=1:length(i_double),
if i==1
x=varargin{i_double(i)};
x=x(:);
maxm=3;
elseif i==2
maxm=varargin{i_double(i)};
if max(size(maxm))>1,
if ~nogui
h=warndlg('The order must be scalar. Using the first value.','Input Parameters');
set(h,props.msgboxwin),h2=guihandles(h);set(h2.OKButton,props.msgbox)
set(h,'Tag','helpdlgbox','HandleVisibility','On');
uiwait(h)
else
warning('The order must be scalar. Using the first value.');
end
end
maxm=maxm(1);
end
end
in_m=maxm;
else
error('No data set found.')
end
if nogui==0 & isempty(findobj('Tag','arfit_Fig'))
action='init';
else action='update';
end
%%%%%% read from the gui
else
% get the handles
nogui=0;
h_fig=findobj('Tag','arfit_fig'); h_fig=h_fig(1);
h_data_axes=findobj('Tag','data_axes','Parent',h_fig);
h_model_axes=findobj('Tag','model_axes','Parent',h_fig);
h_criteria_axes=findobj('Tag','criteria_axes','Parent',h_fig);
h_edit_maxorder=findobj('Tag','edit_maxorder','Parent',h_fig);
h_popup_order=findobj('Tag','popup_order','Parent',h_fig);
h_listbox_coeff=findobj('Tag','listbox_coeff','Parent',h_fig);
h_button_model=findobj('Tag','button_model','Parent',h_fig);
h_button_copyws=findobj('Tag','button_copyws','Parent',h_fig);
h_button_print=findobj('Tag','button_print','Parent',h_fig);
% get values
x=get(h_fig,'UserData');
crit=get(h_criteria_axes,'UserData');
maxm=str2num(get(h_edit_maxorder,'String'));
in_m=get(h_popup_order,'Value');
txt=[repmat('show order ',maxm,1),num2str([1:maxm]'),repmat('|',maxm,1)]';
txt=reshape(txt,1,prod(size(txt)));
set(h_popup_order,'String',txt(1:end-1));
if in_m>maxm
in_m=maxm;
set(h_popup_order,'Value',maxm);
end
show_crit=[];
for k=1:5;
h=findobj('Tag',['criteria',num2str(k)],'Parent',h_fig);
if ~isempty(h);
show_crit=[show_crit k*get(h,'Value')];
end
end
noshow_crit=find(~show_crit);
show_crit=find(show_crit);
action=varargin{1};
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% switch routines
%try
switch(action)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% initialization
case 'init'
h=figure(props.window,... % Plot Figure
'Tag','arfit_fig',...
'MenuBar','Figure',...
'Position',[35.0000 41.3571 129.6667 27.2143],...
'Name','AR Fit',...
'DeleteFcn','arfit close',...
'PaperPosition',[0.25 0.25 7.7677 11.193],...
'PaperType','a4',...
'PaperOrientation','portrait',...
'UserData',x);
set(0,'showhidden','on')
h=findobj('Label','&Help','Type','uimenu');
if isempty(h)
h=uimenu('Label','&Help');
h2=uimenu('Parent',h(1),'Label','&Help Arfit','Callback','helpwin arfit');
else
h1=flipud(get(h(1),'Children'));
set(h1(1),'Separator','on')
h2=uimenu('Parent',h(1),'Label','&Help Arfit','Callback','helpwin arfit'); copyobj(h1,h(1))
delete(h1)
end
set(0,'showhidden','off')
%%%%% logo
h=axes(props.axes,...
'Position',[69 6.5 6.8 3.5]);
logo=load('logo');
h2=imagesc([logo.logo fliplr(logo.logo)]);
set(h2,'Tag','uniLogo')
set(h,props.logo,'Tag','axes_logo')
h=uicontrol(props.text,...
'Tag','text',...
'String','Uni Potsdam',...
'Position',[66 2 22 3.5714]);
h2=textwrap(h,{[char(169),' AGNLD'],'University of Potsdam','2002-2007'});
set(h,'String',h2)
%%%%% data and model axes
% h=uicontrol(props.frame,...
% 'Tag','frame',...
% 'Position',[3.1667 1.2857 58.5000 24.3571]);
h=uicontrol(props.frame,...
'Tag','frame',...
'Position',[3.1667 25.6428 58.5000 .15]);
h=uicontrol(props.text,...
'Tag','text',...
'String','Data and Model Plot');
pos=get(h,'Extent');
set(h,'Position',[5.0000 25.1429-.33 pos(3) pos(4)])
h=axes;
h2=plot(x);
title('Data')
set(h2,'Tag','data_line',props.line)
set(h,props.axes,...
'Tag','data_axes',...
'Position',[6.5000 14.4286 53.5000 8.5]);
h=axes(props.axes,...
'Tag','model_axes',...
'Position',[6.5000 2.7143 53.5000 8.5]);
%%%%% criteria
% h=uicontrol(props.frame,...
% 'Tag','frame',...
% 'Position',[64.8333 16.2857 61.8333 9.3571]);
h=uicontrol(props.frame,...
'Tag','frame',...
'Position',[64.8333 25.6428 61.8333 .15]);
h=uicontrol(props.text,...
'Tag','text',...
'String','Criteria');
pos=get(h,'Extent');
set(h,'Position',[66.3333 25.1429-.33 pos(3) pos(4)])
h=axes('NextPlot','add');
for k=1:5,
h2=plot(0,0,'Tag',['criteria_line',num2str(k)],'Visible','off',props.criteria_line(k));
end
set(h,props.axes,...
'Tag','criteria_axes',...
'Position',[69.8333 18.000 34.3 5.7857]);
h=uicontrol(props.checkbox,...
'Tag','criteria1',...
'ForegroundColor',props.criteria_line(1).Color,...
'String','Variance',...
'Tooltip','Variance of the residues.',...
'Value',1,...
'Callback','arfit criteria',...
'Position',[108.0000 23.3571 17 1.6429]);
h=uicontrol(props.checkbox,... 'Tag','criteria2',...
'ForegroundColor',props.criteria_line(2).Color,...
'String','PACF Crit.',...
'Value',0,...
'Callback','arfit criteria',...
'Tooltip','Partial Auto Correlation Function.',...
'Position',[108.0000 21.7143 17 1.6429]);
h=uicontrol(props.checkbox,...
'Tag','criteria3',...
'ForegroundColor',props.criteria_line(3).Color,...
'String','AIC Criterion',...
'Value',0,...
'Callback','arfit criteria',...
'Tooltip','Akaike''s Information Criterion.',...
'Position',[108.0000 20.1429 17 1.6429]);
h=uicontrol(props.checkbox,...
'Tag','criteria4',...
'String','BIC Criterion',...
'ForegroundColor',props.criteria_line(4).Color,...
'Value',0,...
'Callback','arfit criteria',...
'Tooltip','Bayesian Information Criterion.',...
'Position',[108.0000 18.5000 17 1.6429]);
h=uicontrol(props.checkbox,...
'Tag','criteria5',...
'ForegroundColor',props.criteria_line(5).Color,...
'Tooltip','Criterion asses whether the residues follows white noise.',...
'String','White Noise',...
'Value',0,...
'Callback','arfit criteria',...
'Position',[108.0000 16.8571 17 1.6429]);
% 'Tooltip','Hannan-Quinn Criterion.',...
% 'String','HQ Criterion',...
%%%%% AR coefficients field
% h=uicontrol(props.frame,...
% 'Tag','frame',...
% 'Position',[64.8333 1.2857 61.8333 13.6429]);
h=uicontrol(props.frame,...
'Tag','frame',...
'Position',[64.8333 14.3571 61.8333 .15]);
h=uicontrol(props.text,...
'Tag','text',...
'String','AR Coefficients');
pos=get(h,'Extent');
set(h,'Position',[66.5000 13.8571-.33 pos(3) pos(4)])
h=uicontrol(props.text,...
'Tag','text',...
'String','Max. Order:');
pos=get(h,'Extent');
set(h,'Position',[68.0000 12.08 pos(3) pos(4)])
h=uicontrol(props.edit,...
'Tag','edit_maxorder',...
'Tooltip','Select the maximal order.',...
'String',num2str(maxm),...
'Callback','arfit update',...
'Position',[81.5000 12.2857 5.3333 1.5000]);
in_m=maxm;
txt=[repmat('order ',maxm,1),num2str([1:maxm]'),repmat('|',maxm,1)]';
txt=reshape(txt,1,prod(size(txt)));
h=uicontrol(props.popup,...
'Tag','popup_order',...
'String',txt(1:end-1),...
'Value',maxm,...
'Tooltip','Select the order to show their coefficients.',...
'Callback','arfit update',...
'Enable','off',...
'Position',[88.8333 12.1429 16.5000 1.7143]);
h=uicontrol(props.listbox,...
'Tag','listbox_coeff',... 'String','No Coeffs',...
'Tooltip','AR coefficients of the selected order.',...
'Enable','off',...
'ButtonDownFcn','arfit update',...
'Position',[88.8333 2.3571 16.5000 9.7857]);
h=uicontrol(props.button,...
'Tag','button_help',...
'String','Help',...
'Tooltip','Opens the help window.',...
'Callback','helpwin arfit',...
'Position',[108.0000 2.3571 17 2.0000]);
h=uicontrol(props.button,...
'Tag','button_close',...
'String','Close',...
'Tooltip','Closes this window.',...
'Callback','close',...
'Position',[108.0000 4.71425 17 2.0000]);
h=uicontrol(props.button,...
'Tag','button_model',...
'String','Make Model',...
'Tooltip','Copy model to the workspace.',...
'Callback','arfit make_model',...
'Enable','off',...
'Position',[108.0000 9.42855 17 2.0000]);
h=uicontrol(props.button,...
'Tag','button_copyws',...
'String','To Workspace',...
'Tooltip','Copy coefficients to the Matlab workspace.',...
'Callback','arfit copyws',...
'Enable','off',...
'Position',[108.0000 11.7857 17 2.0000]);
h=uicontrol(props.button,...
'Tag','button_print',...
'String','Print',...
'Tooltip','Print the figure.',...
'Enable','on',...
'Callback','arfit print',...
'Position',[108.0000 7.0714 17 2.0000]);
tags={'arfit_fig';'axes_logo';'frame';'text';'data_axes';'model_axes';'criteria_axes';'criteria1';'criteria2';'criteria3';'criteria4';'criteria5';'edit_maxorder';'popup_order';'listbox_coeff';'button_help';'button_close';'button_model';'button_copyws';'button_print';};
h=[];
for i=1:length(tags); h=[h; findobj('Tag',tags{i})]; end
set(h,'Units','Norm');
arfit update
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% close
case 'close'
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% print
case 'print'
h=[];
h=[h; findobj('Tag','criteria1','Parent',gcf)];
h=[h; findobj('Tag','criteria2','Parent',gcf)];
h=[h; findobj('Tag','criteria3','Parent',gcf)];
h=[h; findobj('Tag','criteria4','Parent',gcf)];
h=[h; findobj('Tag','criteria5','Parent',gcf)];
h=[h; findobj('Tag','button_help','Parent',gcf)];
h=[h; findobj('Tag','button_print','Parent',gcf)];
h=[h; findobj('Tag','button_close','Parent',gcf)];
h=[h; findobj('Tag','button_copyws','Parent',gcf)];
h=[h; findobj('Tag','button_model','Parent',gcf)];
set(h,'Visible','Off')
h2=[];
h2=[h2; findobj('Tag','popup_order','Parent',gcf)];
h2=[h2; findobj('Tag','listbox_coeff','Parent',gcf)];
h2=[h2; findobj('Tag','criteria_axes','Parent',gcf)];
set(h2,'Units','Character')
for k=1:length(h2);
pos(k,:)=get(h2(k),'Position');
set(h2(k),'Position',[pos(k,1:2) pos(k,3)+15 pos(k,4)])
end
set(h_fig,'CurrentAxes',h_criteria_axes);
txt=[{'Var'};{'PACF'};{'AIC'};{'BIC'};{'HQ'};];
h3=[];
for k=1:length(show_crit);
h3=[h3 findobj('Tag',['criteria_line',num2str(show_crit(k))],'Parent',h_criteria_axes)];
end
h4=legend(h3,txt(show_crit),-1);
drawnow
h_dlg=printdlg;
waitfor(h_dlg)
delete(h4)
for k=1:length(h2);
set(h2(k),'Position',pos(k,:))
end
set(h2,'Units','Normalize')
set(h,'Visible','On')
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% show criteria
case 'criteria'
set(h_fig,'CurrentAxes',h_criteria_axes)
h=findobj('Tag','significance_line1','Parent',h_criteria_axes);
signif=get(h,'UserData');
for k=1:length(noshow_crit)
h=findobj('Tag',['criteria_line',num2str(noshow_crit(k))],'Parent',h_criteria_axes);
if ~isempty(h)
set(h,'Visible','Off')
end
end
for k=1:length(show_crit)
h=findobj('Tag',['criteria_line',num2str(show_crit(k))],'Parent',h_criteria_axes);
if isempty(h)
h=plot(1:maxm,crit(:,show_crit(k)), 'Tag',['criteria_line',num2str(show_crit(k))]);
set(h,'Parent',h_criteria_axes,'Tag','criteria_line',props.criteria_line(k),'Visible','On')
set(h_criteria_axes,props.axes,...
'YTickLabel',[],...
'Tag','criteria_axes',...
'Xlim',[1 maxm],...
'Units','Norm',...
'UserData',crit,...
'NextPlot','add')
else
set(h,'YData',crit(:,show_crit(k)),'XData',[1:size(crit,1)],'Visible','On')
end
end
% significance line for PACF
h=findobj('Tag','significance_line1','Parent',h_criteria_axes);
if isempty(h)
h=line([1 maxm],[signif(1) signif(1)])
set(h,props.criteria_line(6),...
'Parent',h_criteria_axes,...
'LineWidth',2,...
'Tag','significance_line1',...
'Color', props.criteria_line(2).Color, ...
'Visible','Off')
else
set(h,'YData',[signif(1) signif(1)],... 'XData',[1 maxm],...
'Visible','Off')
end
if strcmpi(get(findobj('Tag','criteria_line2','Parent',h_criteria_axes),'Visible'),'on')
set(h,'Visible','On')
else
set(h,'Visible','Off')
end
% significance line for Q criterion
h=findobj('Tag','significance_line2','Parent',h_criteria_axes);
if isempty(h)
h=line([1 maxm],[signif(2) signif(2)]);
set(h,props.criteria_line(6),...
'Parent',h_criteria_axes,...
'LineWidth',2,...
'Color', props.criteria_line(5).Color, ...
'Tag','significance_line2',...
'Visible','Off')
else
set(h,'YData',[signif(2) signif(2)],...
'XData',[1 maxm],...
'Visible','Off')
end
if strcmpi(get(findobj('Tag','criteria_line5','Parent',h_criteria_axes),'Visible'),'on')
set(h,'Visible','On')
else
set(h,'Visible','Off')
end
set(h_criteria_axes,'YTickLabel',[],'YLimMode','Auto','XLim',[1 maxm])
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% copy coefficients to the workspace
case 'copyws'
results=get(h_listbox_coeff,'UserData');
a=[results{1}(in_m,1:in_m), results{2}(in_m)];
set(0,'DefaultUIControlBackgroundColor',props.msgbox.BackgroundColor);
answer = inputdlg('The AR coefficients will be stored in the variable:','Copy AR Coefficients',1);
if ~isempty(answer), assignin('base',answer{1},a), end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% copy AR model to the workspace
case 'make_model'
results=get(h_listbox_coeff,'UserData');
a=results{1};
v=results{2};
y=make_model(a,v,in_m,length(x));
%%%% plot the model data
set(h_fig,'CurrentAxes',h_model_axes)
h=findobj('Tag','model_line','Parent',h_model_axes);
if isempty(h)
h=plot(y);
set(h,'Parent',h_model_axes,'Tag','model_line',props.line)
else
set(h,'YData',y,'XData',[1:length(y)])
end
set(h_model_axes,'Tag','model_axes')
title('Model Data')
set(0,'DefaultUIControlBackgroundColor',props.msgbox.BackgroundColor);
answer = inputdlg('The AR model will be stored in the variable:','Copy AR Model',1);
if ~isempty(answer), assignin('base',answer{1},y), end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% update model case 'update'
if ~nogui, setptr(h_fig,'watch'), end
% covariance matrix:
xm=mean(x);N=length(x);
warning off
for k=0:N;
C(k+1)=mean((x(1:N-k)-xm).*(x(1+k:N)-xm))*(N-k)/N;
end
warning on
P(1)=C(1);
a(1,1)=1;
% Levinson-Durbin algorithmus
for m=1:maxm
l=1:m-1;
if m==1
K(1+1)=(C(1+1))/P(1-1+1);
else
K(m+1)=(C(m+1)-sum(a(m-1+1,1+(1:m-1)).*C(m-(1:m-1)+1),2))/P(m-1+1);
end
P(m+1)=(1-K(m+1)^2)*P(m-1+1);
a(m+1,m+1)=K(m+1);
a(m+1,l+1)=a(m-1+1,l+1)-K(m+1)*a(m-1+1,m-l+1);
end
% varianz
for p=1:maxm;
l=1:p;
% V(p)=C(1)-sum(a(p+1,l+1).*C(l+1));
V(p)=C(1)-sum(a(p+1,l+1).^l .*C(l+1));
end
% criterias: 1 - residues variance
% 2 - PACF criteria
% 3 - AIC criteria
% 4 - BIC criteria
% (5 - HQ criteria)
% 5 - Q criteria
crit=zeros(maxm,5);
for m=1:maxm
clear y
% y(i,1)=sum(a(m+1,(1:m)+1)'.*x(i-(m:-1:1)))+V(m)*randn;
% for i=m+1:N; y(i,1)=sum(a(m+1,(1:m)+1)'.*x(i-1:-1:i-m)); end
y=filter([0 a(m+1,(1:m)+1)],1,x);
epsilon=(x-y);
epsilon_mean=mean(epsilon(m:end));
sigma=var(epsilon);
clear rho
for k=1:25;
i=m+1:N-k-1;
rho(k)=sum((epsilon(i+1)-epsilon_mean).*(epsilon(i+k+1)-epsilon_mean))/sum((epsilon(i+1)-epsilon_mean).^2);
end
crit(m,1)=sigma; % Variance of the residues
crit(m,2)=abs(a(m+1,m+1)); % PACF
crit(m,3)=log(sigma)+2*(m)/(N); % AIC
crit(m,4)=log(sigma)+(m)*log(N)/(N); % BIC
% crit(m,5)=log(sigma)+2*(m+1)*5*log(log(N-m))/(N-m);
crit(m,5)=N*sum(rho.^2);
end
% signif(1)=1.96 * std(diag(a(2:end,2:end))) / (max(crit(:,2))-min(crit(:,2))); % significance level for the PACF criterion
signif(1)=1.96 * sqrt(1/N) / (max(crit(:,2))-min(crit(:,2))); % significance level for the PACF criterion
signif(2)=30/(max(crit(:,5))-min(crit(:,5))); % significance level for the Q criterion
for k=1:size(crit,2);crit(:,k)=(crit(:,k)-min(crit(:,k)))/(max(crit(:,k))-min(crit(:,k)));end
y=make_model(a(2:end,2:end),V,in_m,N);
%%%% graphical output
if nogui==0
%%%% enable all disabled objects
set(h_popup_order,'Enable','On')
set(h_listbox_coeff,'Enable','On')
set(h_button_model,'Enable','On')
set(h_button_copyws,'Enable','On')
%%%% show the coefficients
space_max=length(num2str(in_m));
clear txt
for i=1:in_m
space=space_max-length(num2str(i));
txt(i)={['a(',num2str(i),'):',repmat(' ',1,space),sprintf('% 6.4f',a(in_m+1,i+1))]};
end
txt(end+1)={['b: ',repmat(' ',1,space_max+1),sprintf('% 6.4f',V(in_m))]};
set(h_listbox_coeff,'String',txt,'Value',1)
%%%% plot the model data
set(h_fig,'CurrentAxes',h_model_axes)
h=findobj('Tag','model_line','Parent',h_model_axes);
if isempty(h)
h=plot(y);
set(h,'Parent',h_model_axes,'Tag','model_line',props.line)
else
set(h,'YData',y,'XData',[1:length(y)])
end
set(h_model_axes,'Tag','model_axes',props.axes,'Units','Norm')
title('Model Data')
%%%% plot the criteria data
if ~isempty(show_crit)
set(h_fig,'CurrentAxes',h_criteria_axes)
for k=1:length(show_crit)
h=findobj('Tag',['criteria_line',num2str(show_crit(k))],'Parent',h_criteria_axes);
if isempty(h)
h=plot(1:maxm,crit(:,show_crit(k)));
set(h,props.criteria_line(show_crit(k)),...
'Parent',h_criteria_axes,...
'Tag',['criteria_line',num2str(show_crit(k))],...
'Visible','On')
else
set(h,'YData',crit(:,show_crit(k)),...
'XData',[1:size(crit,1)],...
'Visible','On')
end
end
% significance line for PACF criterion
h=findobj('Tag','significance_line1','Parent',h_criteria_axes);
if isempty(h)
h=line([1 maxm],[signif(1) signif(1)]);
set(h,props.criteria_line(6),...
'Parent',h_criteria_axes,...
'Tag','significance_line1',...
'Color', props.criteria_line(2).Color, ...
'UserData',signif,...
'LineWidth',2,...
'Visible','Off')
else
set(h,'YData',[signif(1) signif(1)],...
'XData',[1 maxm],...
'UserData',signif,...
'Visible','Off')
end
if strcmpi(get(findobj('Tag','criteria_line2','Parent',h_criteria_axes),'Visible'),'on') set(h,'Visible','On')
else
set(h,'Visible','Off')
end
% significance line for Q criterion
h=findobj('Tag','significance_line2','Parent',h_criteria_axes);
if isempty(h)
h=line([1 maxm],[signif(2) signif(2)]);
set(h,props.criteria_line(6),...
'Parent',h_criteria_axes,...
'Tag','significance_line2',...
'UserData',signif,...
'Color', props.criteria_line(5).Color, ...
'LineWidth',2,...
'Visible','Off')
else
set(h,'YData',[signif(2) signif(2)],...
'XData',[1 maxm],...
'UserData',signif,...
'Visible','Off')
end
if strcmpi(get(findobj('Tag','criteria_line5','Parent',h_criteria_axes),'Visible'),'on')
set(h,'Visible','On')
else
set(h,'Visible','Off')
end
set(h_criteria_axes,props.axes,...
'Tag','criteria_axes',...
'YTickLabel',[],...
'Xlim',[1 maxm],...
'Ylim',[0 1],...
'UserData',crit,...
'Units','Norm',...
'NextPlot','add')
end
set(h_listbox_coeff,'UserData',{a(2:end,2:end);V})
else
varargout{1}=[a(in_m+1,2:end), V(in_m)];
varargout{2}=y;
end
if ~nogui, setptr(h_fig,'arrow'), end
end
try, set(0,props.root), end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% error handling
if 0
%catch
if ~isempty(findobj('Tag','TMWWaitbar')), delete(findobj('Tag','TMWWaitbar')), end
z=whos;x=lasterr;y=lastwarn;in=varargin{1};
if ischar(in), in2=in; else, in2=[]; end
in=whos('in');
if ~strcmpi(lasterr,'Interrupt')
fid=fopen('error.log','w');
err=fprintf(fid,'%s\n','Please send us the following error report. Provide a brief');
err=fprintf(fid,'%s\n','description of what you were doing when this problem occurred.');
err=fprintf(fid,'%s\n','E-mail or FAX this information to us at:');
err=fprintf(fid,'%s\n',' E-mail: marwan@pik-potsdam.de');
err=fprintf(fid,'%s\n',' Fax: ++49 +331 288 2640');
err=fprintf(fid,'%s\n\n\n','Thank you for your assistance.');
err=fprintf(fid,'%s\n',repmat('-',50,1));
err=fprintf(fid,'%s\n',datestr(now,0));
err=fprintf(fid,'%s\n',['Matlab ',char(version),' on ',computer]);
err=fprintf(fid,'%s\n',repmat('-',50,1));
err=fprintf(fid,'%s\n',x);
err=fprintf(fid,'%s\n',y); err=fprintf(fid,'%s\n',[' during ==> arfit:',action]);
err=fprintf(fid,'%s\n',[' criteria ==> ',num2str(crit)]);
err=fprintf(fid,'%s',[' input ==> ',mat2str(size(x))]);
err=fprintf(fid,'%s\n',[' errorcode ==> no errorcode available']);
err=fprintf(fid,'%s\n',' workspace dump ==>');
if ~isempty(z),
err=fprintf(fid,'%s\n',['Name',char(9),'Size',char(9),'Bytes',char(9),'Class']);
for j=1:length(z);
err=fprintf(fid,'%s\n',[z(j).name,char(9),num2str(z(j).size),char(9),num2str(z(j).bytes),char(9),z(j).class]);
end, end
err=fclose(fid);
disp('------------------------------');
disp(' ERROR OCCURED');
disp(' during executing arfit');
disp('------------------------------');
disp(x);
disp([' during ',action]);
disp('----------------------------');
disp(' Please send us the error report. For your convenience, ')
disp(' this information has been recorded in: ')
disp([' ',fullfile(pwd,'error.log')]), disp(' ')
disp(' Provide a brief description of what you were doing when ')
disp(' this problem occurred.'), disp(' ')
disp(' E-mail or FAX this information to us at:')
disp(' E-mail: marwan@pik-potsdam.de')
disp(' Fax: ++49 +331 288 2640'), disp(' ')
disp(' Thank you for your assistance.')
warning('on')
end
set(0,props.root)
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% sub-programme make AR model
function y=make_model(a,V,in_m,N)
y=filter(V(in_m),[1 -a(in_m,(1:in_m))],randn(N,1));