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offer two alternate methods to compute the skewness and kurtosis, each of which can save substantial computer memory requirements and CPU time in certain applications.
The first approach is to compute the statistical moments by separating the data into bins and then computing the moments from the geometry of the resulting histogram, which effectively becomes a one-pass algorithm for higher moments.
One benefit is that the statistical moment calculations can be carried out to arbitrary accuracy such that the computations can be tuned to the precision of, e. g., the data storage format or the original measurement hardware.
A relative histogram of a random variable can be constructed in

2.135 seconds.