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+## Copyright (C) 2001 Paul Kienzle <pkienzle@users.sf.net>
+##
+## 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/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} mad (@var{x})
+## @deftypefnx{Function File} mad (@var{x}, @var{flag})
+## @deftypefnx{Function File} mad (@var{x}, @var{flag}, @var{dim})
+## Compute the mean/median absolute deviation of @var{x}.
+##
+## The mean absolute deviation is computed as
+##
+## @example
+## mean (abs (@var{x} - mean (@var{x})))
+## @end example
+##
+## and the median absolute deviation is computed as
+##
+## @example
+## median (abs (@var{x} - median (@var{x})))
+## @end example
+##
+## Elements of @var{x} containing NaN or NA values are ignored during computations.
+##
+## If @var{flag} is 0, the absolute mean deviation is computed, and if @var{flag}
+## is 1, the absolute median deviation is computed. By default @var{flag} is 0.
+##
+## This is done along the dimension @var{dim} of @var{x}. If this variable is not
+## given, the mean/median absolute deviation s computed along the smallest dimension of
+## @var{x}.
+##
+## @seealso{std}
+## @end deftypefn
+
+function a = mad (X, flag = 0, dim = [])
+  ## Check input
+  if (nargin < 1)
+    print_usage ();
+  endif
+  if (nargin > 3)
+    error ("mad: too many input arguments");
+  endif
+  
+  if (!isnumeric (X))
+    error ("mad: first input must be numeric");
+  endif
+  
+  if (isempty (dim))
+    dim = min (find (size (X) > 1));
+    if (isempty(dim))
+      dim = 1;
+    endif
+  endif
+  
+  if (!isscalar (flag))
+    error ("mad: second input argument must be a scalar");
+  endif
+  if (!isscalar (dim))
+    error ("mad: dimension argument must be a scalar");
+  endif
+  
+  if (flag == 0)
+    f = @nanmean;
+  else
+    f = @nanmedian;
+  endif
+  
+  ## Compute the mad
+  if (prod(size(X)) != size(X,dim))
+    sz = ones (1, length (size (X)));
+    sz (dim) = size (X,dim);
+    a = f (abs (X - repmat (f (X, dim), sz)), dim);
+  elseif (all (size (X) > 1))
+    a = f (abs (X - ones (size(X, 1), 1) * f (X, dim)), dim);
+  else
+    a = f (abs (X - f(X, dim)), dim);
+  endif
+endfunction
+
+## Tests
+
+%!assert (mad(1), 0);
+%!test
+%! X = eye(3); abs_mean = [4/9, 4/9, 4/9]; abs_median=[0,0,0];
+%! assert(mad(X), abs_mean, eps);
+%! assert(mad(X, 0), abs_mean, eps);
+%! assert(mad(X,1), abs_median);