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通过偏度-峰度集进行推断

Inference via the Skewness‐Kurtosis Set

International Statistical Review · 2025
被引 2 · 同刊同年前 10%
ABS 3

中文导读

研究了峰度减偏度平方这一参数的经验版本的渐近行为,可用于检验单峰性假设,但需谨慎使用,因为该参数对多峰分布也可能取大值。

Abstract

Summary Kurtosis minus squared skewness is bounded from below by 1, but for unimodal distributions, this parameter is bounded by 189/125. In some applications, it is natural to compare distributions by comparing their kurtosis‐minus‐squared‐skewness parameters. The asymptotic behavior of the empirical version of this parameter is studied here for i.i.d. random variables. The result may be used to test the hypothesis of unimodality against the alternative that the kurtosis‐minus‐squared‐skewness parameter is less than 189/125. However, such a test has to be applied with care, because this parameter can take arbitrarily large values, also for multimodal distributions. We also present a test for symmetric unimodality. Simulation results are presented and for three classes of distributions the skewness‐kurtosis sets are described in detail.

统计学统计推断分布形状单峰性