SKEWNESS estimates the skewness 

 y = skewness(x,DIM)
   calculates skewness of x in dimension DIM

 FLAG (default=1): sample skewness
     FLAG=1 returns the "method of moments estimator" [2]
 	  g1 = mean((x-mu)).^3 ./ mean((x-mu).^2).^(3/2)
     FLAG=-1 uses unbiased estimate of std - this was the default before
         introducing the FLAG argument, and available for backwards compatibility.
     FLAG=0 uses unbias estimated for std - this was the default before
         introducing the FLAG argument, and available for backwards compatibility.
 	   mean((x-mu)).^3 ./ std(x).^3

 DIM	dimension
	1: STATS of columns
	2: STATS of rows
	default or []: first DIMENSION, with more than 1 element

 features:
 - can deal with NaN's (missing values)
 - dimension argument 
 - compatible to Matlab and Octave

 see also: SUMSKIPNAN, STATISTIC

 REFERENCE(S):
 [1] https://mathworld.wolfram.com/Skewness.html
 [2] https://en.wikipedia.org/wiki/Skewness
 [3] Joanes, D. N.; Gill, C. A. (1998).
     Comparing measures of sample skewness and kurtosis.
     Journal of the Royal Statistical Society, Series D. 47 (1): 183–189.
     doi:10.1111/1467-9884.00122.
 [4] Doane, David P., and Lori E. Seward.
     Measuring skewness: a forgotten statistic.
     Journal of Statistics Education 19.2 (2011): 1-18. (Page 7)

Package: nan