Lancaster EPrints

A dependence measure for multivariate and spatial extreme values: properties and inference.

Tawn, Jonathan A. and Schlather, Martin (2003) A dependence measure for multivariate and spatial extreme values: properties and inference. Biometrika, 90 (1). pp. 139-156. ISSN 1464-3510

Full text not available from this repository.

Abstract

We present properties of a dependence measure that arises in the study of extreme values in multivariate and spatial problems. For multivariate problems the dependence measure characterises dependence at the bivariate level, for all pairs and all higher orders up to and including the dimension of the variable.Necessary and sufficient conditions are given for subsets of dependence measures to be self-consistent, that is to guarantee the existence of a distribution with such a subset of values for the dependence measure. For pairwise dependence, these conditions are given in terms of positive semidefinite matrices and non-differentiable, positive definite functions. We construct new nonparametric estimators for the dependence measure which, unlike all naive nonparametric estimators, impose these self-consistency properties. As the new estimators provide an improvement on the naive methods, both in terms of the inferential and interpretability properties, their use in exploratory extreme value analyses should aid the identification of appropriate dependence models. The methods are illustrated through an analysis of simulated multivariate data, which shows that a lack of self-consistency is frequently a problem with the existing estimators, and by a spatial analysis of daily rainfall extremes in south-west England, which finds a smooth decay in extremal dependence with distance.

Item Type: Article
Journal or Publication Title: Biometrika
Additional Information: RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research
Uncontrolled Keywords: Dependence measure ; Extreme value ; Max-stable process ; Multivariate extreme-value distribution
Subjects: Q Science > QA Mathematics
Departments: Faculty of Science and Technology > Mathematics and Statistics
ID Code: 2442
Deposited By: ep_importer
Deposited On: 29 Mar 2008 15:50
Refereed?: Yes
Published?: Published
Last Modified: 09 Oct 2013 15:40
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/2442

Actions (login required)

View Item