/usr/share/octave/packages/statistics-1.2.3/mad.m is in octave-statistics 1.2.3-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 | ## 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);
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