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dc.contributor.authorKrupskii, Pavel
dc.contributor.authorGenton, Marc G.
dc.date.accessioned2021-03-21T08:04:49Z
dc.date.available2020-06-29T07:29:33Z
dc.date.available2021-03-21T08:04:49Z
dc.date.issued2021-03-19
dc.date.submitted2020-06-08
dc.identifier.citationKrupskii, P., & Genton, M. G. (2021). Conditional normal extreme-value copulas. Extremes. doi:10.1007/s10687-021-00412-8
dc.identifier.issn1386-1999
dc.identifier.issn1572-915X
dc.identifier.doi10.1007/s10687-021-00412-8
dc.identifier.urihttp://hdl.handle.net/10754/663908
dc.description.abstractWe propose a new class of extreme-value copulas which are extreme-value limits of conditional normal models. Conditional normal models are generalizations of conditional independence models, where the dependence among observed variables is modeled using one unobserved factor. Conditional on this factor, the distribution of these variables is given by the Gaussian copula. This structure allows one to build flexible and parsimonious models for data with complex dependence structures, such as data with spatial dependence or factor structure. We study the extreme-value limits of these models and show some interesting special cases of the proposed class of copulas. We develop estimation methods for the proposed models and conduct a simulation study to assess the performance of these algorithms. Finally, we apply these copula models to analyze data on monthly wind maxima and stock return minima.
dc.description.sponsorshipWe would like to thank the associate editor and two anonymous referees for their constructive comments that helped to improve this paper.
dc.publisherSpringer Nature
dc.relation.urlhttp://link.springer.com/10.1007/s10687-021-00412-8
dc.rightsArchived with thanks to Extremes
dc.titleConditional normal extreme-value copulas
dc.typeArticle
dc.contributor.departmentStatistics Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalExtremes
dc.rights.embargodate2022-03-19
dc.eprint.versionPost-print
dc.contributor.institutionUniversity of Melbourne, Parkville, 3010, Australia.
dc.identifier.arxivid2006.11759
kaust.personGenton, Marc G.
dc.date.accepted2021-01-26
refterms.dateFOA2020-06-29T07:30:46Z


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