Extremes of Gaussian random fields with regularly varying dependence structure
Détails
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Etat: Public
Version: de l'auteur⸱e
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
ISSN
1386-1999
1572-915X
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
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Création de la notice
31/05/2016 12:41
Dernière modification de la notice
20/08/2019 16:14