dc.contributor.author | Strokorb, Kirstin | |
dc.contributor.author | Oesting, Marco | |
dc.contributor.author | De Fondeville, Raphaël | |
dc.date.accessioned | 2025-02-06T10:04:15Z | |
dc.date.available | 2025-02-06T10:04:15Z | |
dc.date.issued | 2025-02 | |
dc.identifier.uri | http://publications.mfo.de/handle/mfo/4206 | |
dc.description.abstract | Threshold exceedances of stochastic processes in space and time often appear to be more localized the more extreme they are. While classical regularly varying stochastic processes cannot model this effect, we introduce an adapted version of regular variation, where a suitable domain-scaling can be incorporated to accommodate this behaviour. Our theory is inspired by the triangular array convergence of domain-scaled maxima of Gaussian processes to a Brown-Resnick process and turns out to be natural in this context. We study key properties of the resulting tail process and demonstrate its ability to approximate conditional exceedance probabilities of Gaussian processes. Mathematical convenience arises from the recently rediscovered concept of vague convergence based on boundedness. | en_US |
dc.description.sponsorship | The authors would like to thank the Mathematisches Forschungsinstitut Oberwolfach for the kind hospitality during our two weeks at the institute in March 2024 supported through the program "Oberwolfach Research Fellows", which has allowed us to kickstart this research. KS wishes to thank her home institution, Cardiff University, for granting her research leave in autumn 2024 to complete the research and writing of this manuscript, including financial support for visiting MO at the University of Stuttgart during this time. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Mathematisches Forschungsinstitut Oberwolfach | en_US |
dc.relation.ispartofseries | Oberwolfach Preprints;2025-02 | |
dc.title | Domain-Scaled Regular Variation: Mathematical Foundations for a New Tail Process | en_US |
dc.type | Preprint | en_US |
dc.rights.license | Dieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. | de |
dc.rights.license | This document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties. | en |
dc.identifier.doi | 10.14760/OWP-2025-02 | |
local.scientificprogram | OWRF 2024 | en_US |
local.series.id | OWP-2025-02 | en_US |
dc.identifier.ppn | 1917638620 | |