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# wskewness

## PURPOSE

Computes sample skewness

## SYNOPSIS

s = wskewness(X,dim)

## DESCRIPTION

``` WSKEWNESS Computes sample skewness

CALL:  k = wskewness(X,dim);

k = sample skewness (third central moment divided by second^(3/2))
X = data vector or matrix
dim = dimension to sum across. (default 1'st non-singleton
dimension of X)

Example:
R=wgumbrnd(2,2,[],100,2);
wskewness(R)

## CROSS-REFERENCE INFORMATION

This function calls:
 error Display message and abort function. mean Average or mean value.
This function is called by:
 Chapter2 % CHAPTER2 Modelling random loads and stochastic waves dat2tr Estimate transformation, g, from data.

## SOURCE CODE

```001 function s = wskewness(X,dim)
002 %WSKEWNESS Computes sample skewness
003 %
004 % CALL:  k = wskewness(X,dim);
005 %
006 %        k = sample skewness (third central moment divided by second^(3/2))
007 %        X = data vector or matrix
008 %      dim = dimension to sum across. (default 1'st non-singleton
009 %                                              dimension of X)
010 %
011 % Example:
012 %   R=wgumbrnd(2,2,[],100,2);
013 %   wskewness(R)
014 %
016
017 % Tested on: Matlab 5.3
018 % History:
019 % revised pab 24.10.2000
020 % - made it more general: accepts any size of X
021 % - added dim, nargchk
023
024 error(nargchk(1,2,nargin))
025 sz = size(X);
026 if nargin<2|isempty(dim),
027   % Use 1'st non-singleton dimension or dimension 1
028   dim = min(find(sz~=1));
029   if isempty(dim), dim = 1; end
030 end
031
032 rsz = ones(size(sz)); rsz(dim)=sz(dim);
033 mu  = mean(X,dim);
034 mu  = repmat(mu,rsz); % reshape mu to the size of X
035 s   = mean((X-mu).^3,dim)./mean((X-mu).^2,dim).^(3/2);
036
037
038
039```

Mathematical Statistics
Centre for Mathematical Sciences
Lund University with Lund Institute of Technology

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