mad
              Compute the mean or median absolute deviation (MAD) of the elements of x.
The mean absolute deviation is defined as
| mad = mean (abs (x - mean (x))) | 
The median absolute deviation is defined as
| mad = median (abs (x - median (x))) | 
 If x is a vector, compute mad for each element in x.  If
 x is an array the calculation is performed over the first
 non-singleton dimension.
 mad excludes NaN values from calculation similar to using the
 omitnan option in var, mean, and median.
The optional argument opt determines whether mean or median absolute deviation is calculated. The default is 0 which corresponds to mean absolute deviation; a value of 1 corresponds to median absolute deviation. Passing an empty input [] defaults to mean absolute deviation (opt = 0).
 The optional argument dim forces mad to operate along the
 specified dimension.  Specifying any singleton dimension in x,
 including any dimension exceeding ndims (x), will result in
 an output of 0.
 Specifying the dimension as vecdim, a vector of non-repeating
 dimensions, will return the mad over the array slice defined by
 vecdim.  If vecdim indexes all dimensions of x, then it is
 equivalent to the option "all".  Any dimension included in
 vecdim greater than ndims (x) is ignored.
 Specifying the dimension as "all" will force mad to operate
 on all elements of x, and is equivalent to mad (x(:)).
 As a measure of dispersion, mad is less affected by outliers than
 std.
 See also: 
bounds, 
range, 
iqr, 
  std, 
  mean, 
  median
Source Code: mad