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A semi-parametric Bayesian extreme value model using a Dirichlet process mixture of gamma densities

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  • Jairo Alberto Fúquene Pati�o

Abstract

In this paper, we propose a model with a Dirichlet process mixture of gamma densities in the bulk part below threshold and a generalized Pareto density in the tail for extreme value estimation. The proposed model is simple and flexible for posterior density estimation and posterior inference for high quantiles. The model works well even for small sample sizes and in the absence of prior information. We evaluate the performance of the proposed model through a simulation study. Finally, the proposed model is applied to a real environmental data.

Suggested Citation

  • Jairo Alberto Fúquene Pati�o, 2015. "A semi-parametric Bayesian extreme value model using a Dirichlet process mixture of gamma densities," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(2), pages 267-280, February.
  • Handle: RePEc:taf:japsta:v:42:y:2015:i:2:p:267-280
    DOI: 10.1080/02664763.2014.947357
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