--- /dev/null
+function y=var(x,opt,DIM,W)
+% VAR calculates the variance.
+%
+% y = var(x [, opt[, DIM]])
+% calculates the variance in dimension DIM
+% the default DIM is the first non-single dimension
+%
+% opt 0: normalizes with N-1 [default]
+% 1: normalizes with N
+% DIM dimension
+% 1: VAR of columns
+% 2: VAR of rows
+% N: VAR of N-th dimension
+% default or []: first DIMENSION, with more than 1 element
+% W weights to compute weighted variance (default: [])
+% if W=[], all weights are 1.
+% number of elements in W must match size(x,DIM)
+%
+% usage:
+% var(x)
+% var(x, opt, DIM)
+% var(x, [], DIM)
+% var(x, W, DIM)
+% var(x, opt, DIM, W)
+%
+% features:
+% - can deal with NaN's (missing values)
+% - weighting of data
+% - dimension argument
+% - compatible to Matlab and Octave
+%
+% see also: MEANSQ, SUMSQ, SUMSKIPNAN, MEAN, RMS, STD,
+
+% 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 3 of the License, or
+% (at your option) any later version.
+%
+% This program is distributed in the hope that it will be useful,
+% but WITHOUT ANY WARRANTY; without even the implied warranty of
+% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+% GNU General Public License for more details.
+%
+% You should have received a copy of the GNU General Public License
+% along with this program; If not, see <http://www.gnu.org/licenses/>.
+
+% $Id: var.m 8223 2011-04-20 09:16:06Z schloegl $
+% Copyright (C) 2000-2003,2006,2009,2010 by Alois Schloegl <alois.schloegl@gmail.com>
+% This is part of the NaN-toolbox for Octave and Matlab
+% http://pub.ist.ac.at/~schloegl/matlab/NaN/
+
+if nargin<3,
+ DIM = [];
+end;
+
+if nargin==1,
+ W = [];
+ opt = [];
+
+elseif any(nargin==[2,3])
+ if (numel(opt)<2),
+ W = [];
+ else
+ W = opt;
+ opt = [];
+ end;
+elseif (nargin==4) && (numel(opt)<2) && (numel(DIM)<2),
+ ;
+else
+ fprintf(1,'Error VAR: incorrect usage\n');
+ help var;
+ return;
+end;
+
+if isempty(opt),
+ opt = 0;
+end;
+
+if isempty(DIM),
+ DIM = find(size(x)>1,1);
+ if isempty(DIM), DIM=1; end;
+end;
+
+[y,n,ssq] = sumskipnan(x,DIM,W);
+if all(ssq(:).*n(:) > 2*(y(:).^2)),
+ %% rounding error is neglectable
+ y = ssq - y.*y./n;
+else
+ %% rounding error is not neglectable
+ szx = size(x);
+ szy = size(y);
+ if length(szy)<length(szx);
+ szy(length(szy)+1:length(szx)) = 1;
+ end;
+ [y,n] = sumskipnan((x-repmat(y./n,szx./szy)).^2,DIM,W);
+end;
+
+if (opt~=1)
+ n = max(n-1,0); % in case of n=0 and n=1, the (biased) variance, STD and STE are INF
+end;
+y = y./n; % normalize
+