A log probability weighted moment estimator of extreme quantiles

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1 Citation (Scopus)

Abstract

In this paper we consider the semi-parametric estimation of extreme quantiles of a right heavy-tail model. We propose a new Probability Weighted Moment estimator for extreme quantiles, which is obtained from the estimators of the shape and scale parameters of the tail. Under a second-order regular variation condition on the tail, of the underlying distribution function, we deduce the non degenerate asymptotic behaviour of the estimators under study and present an asymptotic comparison at their optimal levels. In addition, the performance of the estimators is illustrated through an application to real data.

Original languageEnglish
Title of host publicationTheory and Practice of Risk Assessment - ICRA5 2013
PublisherSpringer New York LLC
Pages293-303
Number of pages11
Volume136
ISBN (Electronic)978-331918028-1
DOIs
Publication statusPublished - 2015
Event5th International Conference on Risk Analysis, ICRA5 2013 - Tomar, Portugal
Duration: 30 May 20131 Jun 2013

Conference

Conference5th International Conference on Risk Analysis, ICRA5 2013
CountryPortugal
CityTomar
Period30/05/131/06/13

Keywords

  • Extreme quantile
  • Extreme value index
  • Log probability weighted moment
  • Optimal level
  • Statistics of extremes

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