X-Git-Url: https://git.creatis.insa-lyon.fr/pubgit/?p=CreaPhase.git;a=blobdiff_plain;f=octave_packages%2Fnan-2.5.5%2FzScoreMedian.m;fp=octave_packages%2Fnan-2.5.5%2FzScoreMedian.m;h=903f77138a3d7c8e13b15d87d46bfab9cecb970c;hp=0000000000000000000000000000000000000000;hb=f5f7a74bd8a4900f0b797da6783be80e11a68d86;hpb=1705066eceaaea976f010f669ce8e972f3734b05

diff --git a/octave_packages/nan-2.5.5/zScoreMedian.m b/octave_packages/nan-2.5.5/zScoreMedian.m
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+function Z = zScoreMedian(X, DIM)
+% zScoreMedian removes the median and standardizes by the 1.483*median absolute deviation
+%
+% Usage:  Z = zScoreMedian(X, DIM)
+% Input:  X  : data
+%         DIM: dimension along which z-score should be calculated (1=columns, 2=rows) 
+%              (optional, default=first dimension with more than 1 element
+% Output: Z  : z-scores
+
+%	Copyright (C) 2003 Patrick Houweling
+%	Copyright (C) 2009 Alois Schloegl
+%	$Id: zScoreMedian.m 8075 2011-01-27 17:10:36Z schloegl $
+%       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 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/>.
+
+
+% input checks
+if any(size(X)==0), 
+	return; 
+end;
+
+% robust moment estimators: 
+% - mean: median
+% - standard deviation: 1.483 * median absolute deviation (medAbsDev);
+%   the factor 1.483 is the ratio of the standard deviation of a normal random variable to its MAD.
+if nargin<2,
+        [D, M] = medAbsDev(X);
+else
+        [D, M] = medAbsDev(X, DIM);
+end;
+
+% z-score: subtract M and divide by 1.483*D
+Z = (X - repmat(M, size(X)./size(M))) ./ repmat(1.483*D, size(X)./size(D));