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