Extremes of Gaussian random fields with regularly varying dependence structure

Details

Ressource 1Download: BIB_AAB79CDAAC9F.P001.pdf (562.85 [Ko])
State: Public
Version: author
Serval ID
serval:BIB_AAB79CDAAC9F
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Extremes of Gaussian random fields with regularly varying dependence structure
Journal
Extremes
Author(s)
Debiicki K., Hashorva E., Liu P.
ISSN
1386-1999
1572-915X
Publication state
Published
Issued date
06/2017
Peer-reviewed
Oui
Volume
20
Number
2
Pages
333-392
Language
english
Abstract
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.
Keywords
Statistics and Probability, Engineering (miscellaneous), Economics, Econometrics and Finance (miscellaneous)
Web of science
Create date
31/05/2016 11:41
Last modification date
20/08/2019 15:14
Usage data