--- a/extra/tsa/INDEX	Tue Apr 15 07:56:25 2003 +0000
+++ b/extra/tsa/INDEX	Tue Apr 15 08:02:25 2003 +0000
@@ -21,11 +21,11 @@
    ar_spa
    detrend
    flix
-   quantiles
 
 Multivariate analysis
    mvar
    mvfilter
+   mvfreqz
    arfit2    
 
 Adaptive (time-varying) analysis

--- a/extra/tsa/quantiles.m	Tue Apr 15 07:56:25 2003 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,94 +0,0 @@
-function Q=quantiles(Y,q)
-% QUANTILES calculates the quantiles of histograms or sample arrays.  
-%
-%  Q = quantiles(Y,q)      
-%     returns the q-th quantile of each column of sample array Y
-%
-%  Q = quantiles(HIS,q)
-%     returns the q-th quantile from the histogram HIS. 
-%     HIS must be a HISTOGRAM struct as defined in HISTO2 or HISTO3.
-%
-% If q is a vector, the each row of Q returns the q(i)-th quantile 
-%
-% see also: FLIX, HISTO2, HISTO3
-
-% QUANTILES demonstrates how to calculate quantiles 
-%
-% q-quantile Q of data series Y 
-% (1) explicite form
-%	tmp=sort(Y);
-%	N=sum(~isnan(Y));
-%	Q = flix(tmp,N*q + 0.5);
-%
-% (2) in 1 line
-%	Q = flix(sort(Y),sum(~isnan(Y))*q + 0.5);
-%
-% (3) q-quantile Q of histogram H with bins t
-%	tmp=HISTOG>0;
-%	HISTOG=full(HISTOG(tmp));
-%	t = t(tmp);
-%	N = sum(HISTOG);
-%	tmp = cumsum(HISTOG)-N*q;
-%
-%	if ~any(~tmp), 
-%		Q(k) = t(find(diff(sign(tmp)))+1);
-%	else
-%		Q(k) = mean(t(find(~tmp)+(0:1)));
-%	end;	
-
-%	$Revision$
-%	$Id$
-%	last revision 13 Mar.2003
-%	Copyright (c) 1996-2003 by Alois Schloegl
-%	e-mail: a.schloegl@ieee.org	
-
-
-if nargin<2,
-	help quantiles
-        
-else
-        SW = isstruct(Y);
-        if SW, SW = isfield(Y,'datatype'); end;
-        if SW, SW = strcmp(Y.datatype,'HISTOGRAM'); end;
-        if SW,                 
-                [yr,yc]=size(Y.H);
-                Q = repmat(nan,length(q),yc);
-                if ~isfield(Y,'N');
-                        Y.N = sum(Y.H,1);
-                end;
-                
-                for k1=1:yc,
-                        tmp=Y.H(:,k1)>0;
-                        h=full(Y.H(tmp,k1));
-                        t = Y.X(tmp,min(size(Y.X,2),k1));
-                        for k2 = 1:length(q),
-                                tmp = cumsum(h)-Y.N(k1)*q(k2);
-                                if ~any(~tmp), 
-                                        Q(k2,k1) = t(find(diff(sign(tmp)))+1);
-                                else
-                                        Q(k2,k1) = mean(t(find(~tmp)+(0:1)));
-                                end;	        
-                        end
-                end;
-                
-        elseif isnumeric(Y),
-                [yr,yc] = size(Y);
-                Q = repmat(nan,length(q),yc);
-                N = sum(~isnan(Y),1);
-                Y(isnan(Y)) = inf;   % making sure NaN's are at the end;
-                Y = sort(Y,1);
-                for k1 = 1:yc,
-	                for k2 = 1:length(q),
-				Q(k2,k1) = flix(Y(:,k1),N(k1)*q(k2) + 0.5);                	        
-                	end;
-                end;
-                
-        else
-                fprintf(2,'Error QUANTILES: invalid input argument\n');
-                return;
-        end;
-        
-end;
-
-
-