Research Article

On the construction of multivariate extreme value models via copulas

  1. F. Durante1,*,
  2. G. Salvadori2,*

Article first published online: 3 JUN 2009

DOI: 10.1002/env.988

Issue

Environmetrics

Environmetrics

Volume 21, Issue 2, pages 143–161, March 2010

Additional Information

How to Cite

Durante, F. and Salvadori, G. (2010), On the construction of multivariate extreme value models via copulas. Environmetrics, 21: 143–161. doi: 10.1002/env.988

Author Information

  1. 1

    Department of Knowledge-Based Mathematical Systems, Johannes Kepler University, Altenbergerstraβe 69, A-4040 Linz, Austria

  2. 2

    Dipartimento di Matematica, Università del Salento, Provinciale Lecce-Arnesano, P.O. Box 193, I-73100 Lecce, Italy

*Department of Knowledge-Based Mathematical Systems, Johannes Kepler University, Altenbergerstraβe 69, A-4040 Linz, Austria.

Publication History

  1. Issue published online: 17 MAR 2010
  2. Article first published online: 3 JUN 2009
  3. Manuscript Accepted: 22 DEC 2008
  4. Manuscript Received: 25 SEP 2008

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Keywords:

  • multivariate extreme value distributions;
  • extreme value copulas;
  • Marshall--Olkin models;
  • random variates generation;
  • multivariate return periods

Abstract

Copulas represent a fundamental tool for constructing multivariate probability distributions. Exploiting recent theoretical developments concerning the construction of copulas, we outline several methods for generating multivariate extreme value (MEV) laws having a suitable number of parameters, a feature of great importance in applications. The corresponding random vectors can be efficiently simulated, and easily fitted to empirical data. The use of multivariate return periods for extreme events is also discussed. A practical illustration involving maxima sampled via a network of non-independent gauge stations is presented. Copyright © 2009 John Wiley & Sons, Ltd.

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