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