Extremes of Gaussian random fields with regularly varying dependence structure

Détails

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Etat: Public
Version: de l'auteur⸱e
ID Serval
serval:BIB_AAB79CDAAC9F
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Extremes of Gaussian random fields with regularly varying dependence structure
Périodique
Extremes
Auteur⸱e⸱s
Debiicki K., Hashorva E., Liu P.
ISSN
1386-1999
1572-915X
Statut éditorial
Publié
Date de publication
06/2017
Peer-reviewed
Oui
Volume
20
Numéro
2
Pages
333-392
Langue
anglais
Résumé
Let be a centered Gaussian random field with variance function sigma (2)(ai...) that attains its maximum at the unique point , and let . For a compact subset of a"e, the current literature explains the asymptotic tail behaviour of under some regularity conditions including that 1 - sigma(t) has a polynomial decrease to 0 as t -> t (0). In this contribution we consider more general case that 1 - sigma(t) is regularly varying at t (0). We extend our analysis to Gaussian random fields defined on some compact set , deriving the exact tail asymptotics of for the class of Gaussian random fields with variance and correlation functions being regularly varying at t (0). A crucial novel element is the analysis of families of Gaussian random fields that do not possess locally additive dependence structures, which leads to qualitatively new types of asymptotics.
Mots-clé
Statistics and Probability, Engineering (miscellaneous), Economics, Econometrics and Finance (miscellaneous)
Web of science
Création de la notice
31/05/2016 12:41
Dernière modification de la notice
20/08/2019 16:14
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