--- /dev/null
+function [d] = mahal(X,Y)
+% MAHAL return the Mahalanobis' D-square distance between the
+% multivariate samples x and y, which must have the same number
+% of components (columns), but may have a different number of observations (rows).
+%
+% d = mahal(X,Y)
+%
+% d(k) = (X(k,:)-MU)*inv(SIGMA)*(X(k,:)-MU)'
+%
+% where MU and SIGMA are the mean and the covariance matrix of Y
+%
+%
+% see also: TRAIN_SC, TEST_SC, COVM
+%
+% References:
+
+% $Id: train_sc.m 2140 2009-07-02 12:03:55Z schloegl $
+% Copyright (C) 2009 by Alois Schloegl <alois.schloegl@gmail.com>
+% This function is part of the NaN-toolbox
+% http://pub.ist.ac.at/~schloegl/matlab/NaN/
+
+% 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 (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, write to the Free Software
+% Foundation, Inc., 51 Franklin Street - Fifth Floor, Boston, MA 02110-1301, USA.
+
+sx = size(X);
+sy = size(Y);
+
+if sx(2)~=sy(2),
+ error('number of columns of X and Y do not fit');
+end;
+
+IR = inv(covm(Y,'E'));
+IR(1,1) = IR(1,1)-1;
+
+D = [ones(size(X,1),1),X];
+d = sum((D*IR).*D,2);
+