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一种另类的偏态指数幂分布公式。

An Alternative Skew Exponential Power Distribution Formulation.

作者信息

Hutson Alan D

机构信息

Roswell Park Cancer Institute, Department of Biostatistics and Bioinformatics, Elm and Carlton Streets, Buffalo, NY 14623.

出版信息

Commun Stat Theory Methods. 2019;48(12):3005-3024. doi: 10.1080/03610926.2018.1473600. Epub 2018 Nov 22.

Abstract

In this note we propose a newly formulated skew exponential power distribution that behaves substantially better than previously defined versions. This new model performs very well in terms of the large sample behavior of the maximum likelihood estimation procedure when compared to the classically defined four parameter model defined by Azzalini (1986). More recently, approaches to defining a skew exponential power distribution have used five or more parameters. Our approach improves upon previous attempts to extend the symmetric power exponential family to include skew alternatives by maintaining a minimum set of four parameters corresponding directly to location, scale, skewness and kurtosis. We illustrate the utility of our proposed model using translational and clinical data sets.

摘要

在本笔记中,我们提出了一种新构建的偏态指数幂分布,其表现比先前定义的版本要好得多。与Azzalini(1986)定义的经典四参数模型相比,这个新模型在最大似然估计过程的大样本行为方面表现非常出色。最近,定义偏态指数幂分布的方法使用了五个或更多参数。我们的方法改进了先前将对称幂指数族扩展以纳入偏态替代方案的尝试,通过保持直接对应于位置、尺度、偏度和峰度的最少四个参数集。我们使用转化和临床数据集说明了我们提出的模型的效用。

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本文引用的文献

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A Cautionary Note on Beta Families of Distributions and the Aliases Within.
Am Stat. 2018;72(2):121-129. doi: 10.1080/00031305.2016.1213661. Epub 2018 Jan 26.
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Testing for normality.
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