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arXiv · 1712.02183

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

Diego Marcondes·Cláudia Peixoto·Ana Carolina Maia
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Abstract

In this survey we present an extensive research of the vast literature about the Generalized Lambda Distribution (GLD) and propose a hurdle, or two-way, model whose associated distribution is the GLD in order to meet the demand for a highly flexible model of heavy-tailed data with excess of zeros. We apply the developed models to a dataset consisting of yearly healthcare expenses, a typical example of heavy-tailed data with excess of zeros. The fitted models are compared with models based on the Generalised Pareto Distribution and it is established that the GLD models perform best.

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Diego Marcondes, Cláudia Peixoto, Ana Carolina Maia. 2017-12-06. A survey of a hurdle model for heavy-tailed data based on the generalized lambda distribution. https://doi.org/10.1080/03610926.2018.1549251

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