A survey of a hurdle model for heavy-tailed data based on the generalized lambda distribution

D. Marcondes, C. Peixoto and A. C. Maia

Communications in Statistics - Theory and Methods, 2020, vol. 49, issue 4, 781-808

Abstract: We present a literature review on the current state of Generalized Lambda Distribution (GλD) research and propose a highly flexible GλD hurdle model for heavy tailed data with excessive zeros. We apply the developed models to a dataset consisting of yearly healthcare expenses, a typical example of heavy-tailed data with excessive zeros. The fitted GλDs are compared with models based on the Generalised Pareto Distribution and it is established that the GλD performs the best.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:49:y:2020:i:4:p:781-808

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DOI: 10.1080/03610926.2018.1549251

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