Exponentiated generalized Pareto distribution: Properties and applications towards extreme value theory

Seyoon Lee and Joseph H. T. Kim

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 8, 2014-2038

Abstract: The GPD is a central distribution in modelling heavy tails in many applications. Applying the GPD to actual datasets however is not trivial. In this paper we propose the Exponentiated GPD (exGPD), created via log-transform of the GPD variable, which has less sample variability. Various distributional quantities of the exGPD are derived analytically. As an application we also propose a new plot based on the exGPD as an alternative to the Hill plot to identify the tail index of heavy tailed datasets, and carry out simulation studies to compare the two.

Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1080/03610926.2018.1441418

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