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A Folding Method for Extreme Quantiles Estimation

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Resumo:In order to estimate extreme quantiles from independent and identically distributed random variables, we propose and study a novel folding procedure that improves quantile estimates obtained from the classical Peaks-Over-Threshold method (POT) used in Extreme Value Theory. The idea behind the folding approach is to connect the part of a distribution above a given threshold with the one below it. A simplified version of this approach was studied by You et al. (2010). In this paper, an extension based on two thresholds is proposed to better combine the folding scheme with the POT approach. Simulations indicate that this new strategy leads to improved extreme quantiles estimates for finite samples. Asymptotic normality of the folded POT estimators is also derived.
Autores principais:Guillou , Armelle
Outros Autores:Naveau , Philippe; You , Alexandre
Assunto:extreme quantile estimation peaks-over-thresholds generalized Pareto distribution folding generalized probability-weighted moments estimators
Ano:2010
País:Portugal
Tipo de documento:artigo
Tipo de acesso:unknown
Instituição associada:Instituto Nacional de Estatística
Idioma:inglês
Origem:REVSTAT-Statistical Journal

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