statsmodels.stats.stattools.expected_robust_kurtosis

statsmodels.stats.stattools.expected_robust_kurtosis(ab=(5.0, 50.0), dg=(2.5, 25.0)) [source]

Calculates the expected value of the robust kurtosis measures in Kim and White assuming the data are normally distributed.

Parameters:	ab (iterable, optional) – Contains 100*(alpha, beta) in the kr3 measure where alpha is the tail quantile cut-off for measuring the extreme tail and beta is the central quantile cutoff for the standardization of the measure db (iterable, optional) – Contains 100*(delta, gamma) in the kr4 measure where delta is the tail quantile for measuring extreme values and gamma is the central quantile used in the the standardization of the measure
Returns:	ekr – Contains the expected values of the 4 robust kurtosis measures
Return type:	array, 4-element

Notes

See robust_kurtosis for definitions of the robust kurtosis measures