Linking representations for multivariate extremes via a limit set

Nolde, Natalia and Wadsworth, Jennifer (2022) Linking representations for multivariate extremes via a limit set. Advances in Applied Probability, 54 (3). pp. 688-717. ISSN 0001-8678

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Abstract

The study of multivariate extremes is dominated by multivariate regular variation, although it is well known that this approach does not provide adequate distinction between random vectors whose components are not always simultaneously large. Various alternative dependence measures and representations have been proposed, with the most well-known being hidden regular variation and the conditional extreme value model. These varying depictions of extremal dependence arise through consideration of different parts of the multivariate domain, and particularly exploring what happens when extremes of one variable may grow at different rates to other variables. Thus far, these alternative representations have come from distinct sources and links between them are limited. In this work we elucidate many of the relevant connections through a geometrical approach. In particular, the shape of the limit set of scaled sample clouds in light-tailed margins is shown to provide a description of several different extremal dependence representations.

Item Type:
Journal Article
Journal or Publication Title:
Advances in Applied Probability
Additional Information:
https://www.cambridge.org/core/journals/advances-in-applied-probability/article/linking-representations-for-multivariate-extremes-via-a-limit-set/9A77F8E10602DC13EA26E429CFB5FD21 The final, definitive version of this article has been published in the Journal, Advances in Applied Probability, 54 (3), pp 688-717 2022, © 2022 Cambridge University Press.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2604
Subjects:
?? multivariate extreme value theoryconditional extremeshidden regular variationlimit setasymptotic (in)dependenceapplied mathematicsstatistics and probability ??
ID Code:
158565
Deposited By:
Deposited On:
19 Aug 2021 08:35
Refereed?:
Yes
Published?:
Published
Last Modified:
09 May 2024 09:45