k = kurtosis(X) returns the sample kurtosis of X. For vectors, kurtosis(x) is the kurtosis of the elements in the vector x. For matrices kurtosis(X) returns the sample kurtosis for each column of X. For N-dimensional arrays, kurtosis operates along the first nonsingleton dimension of X.
k = kurtosis(X,flag) specifies whether to correct for bias (flag is 0) or not (flag is 1, the default). When X represents a sample from a population, the kurtosis of X is biased, that is, it will tend to differ from the population kurtosis by a systematic amount that depends on the size of the sample. You can set flag to 0 to correct for this systematic bias.
k = kurtosis(X,flag,dim) takes the kurtosis along dimension dim of X.
kurtosis treats NaNs as missing values and removes them.
