KURTOSIS estimates the kurtosis y = kurtosis(x, FLAG, DIM) calculates kurtosis of x in dimension DIM FLAG (default=1): FLAG=1 returns the "method of moments estimator" [2] k2 = mean((x-mu)).^4 ./ mean((x-mu).^2).^2 = g2+3 = m4/m2^2 FLAG=0 uses the "Standard unbiased estimator" (according to [2,3]) and returns [(n+1)*g2+6]*(n-1)/((n-2)*(n-3)) + 3 FLAG=-1 uses unbiased estimate of std - this was the default before introducing the FLAG argument, and available for backwards compatibility. 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, VAR, STD, VAR, SKEWNESS, MOMENT, STATISTIC, IMPLICIT_SKIP_NAN REFERENCE(S): [1] https://mathworld.wolfram.com/Kurtosis.html [2] https://en.wikipedia.org/wiki/Kurtosis [3] Joanes, Derrick N.; Gill, Christine 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, JSTOR 2988433
Package: nan