A default Bayesian procedure for the generalized Pareto distribution

被引:52
作者
Castellanos, M. Eugenia
Cabras, Stefano
机构
[1] Rey Juan Carlos Univ, Dept Stat & Operat Res, Madrid 28933, Spain
[2] Univ Cagliari, Dept Math, I-09124 Cagliari, Italy
关键词
Bayesian inference; extreme value theory; Jeffreys's prior; peaks over the threshold;
D O I
10.1016/j.jspi.2006.01.006
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The generalized Pareto distribution is used to model the exceedances over a threshold in a number of fields, including the analysis of environmental extreme events and financial data analysis. We use this model in a default Bayesian framework where no prior information is available on unknown model parameters. Using a large simulation study, we compare the performance of our posterior estimations of parameters with other methods proposed in the literature. We show that our procedure also allows to make inferences in other quantities of interest in extreme value analysis without asymptotic arguments. We apply the proposed methodology to a real data set. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:473 / 483
页数:11
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