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.
Bibliographical noteFunding Information:
This research is supported by Basic Science Research Program of the National Research Foundation of Korea (NRF-2015R1A1A1A05027336)
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All Science Journal Classification (ASJC) codes
- Statistics and Probability