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dc.contributor.authorXu, Ganggang
dc.contributor.authorGenton, Marc G.
dc.date.accessioned2017-01-02T09:08:27Z
dc.date.available2017-01-02T09:08:27Z
dc.date.issued2016-09-21
dc.identifier.citationXu G, Genton MG (2016) Tukey max-stable processes for spatial extremes. Spatial Statistics 18: 431–443. Available: http://dx.doi.org/10.1016/j.spasta.2016.09.002.
dc.identifier.issn2211-6753
dc.identifier.doi10.1016/j.spasta.2016.09.002
dc.identifier.urihttp://hdl.handle.net/10754/622346
dc.description.abstractWe propose a new type of max-stable process that we call the Tukey max-stable process for spatial extremes. It brings additional flexibility to modeling dependence structures among spatial extremes. The statistical properties of the Tukey max-stable process are demonstrated theoretically and numerically. Simulation studies and an application to Swiss rainfall data indicate the effectiveness of the proposed process. © 2016 Elsevier B.V.
dc.publisherElsevier BV
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S2211675316300574
dc.subjectBrown-Resnick process
dc.subjectComposite likelihood
dc.subjectExtremal coefficient
dc.subjectExtremal-t process
dc.subjectGeometric Gaussian process
dc.subjectMax-stable process
dc.titleTukey max-stable processes for spatial extremes
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentStatistics Program
dc.identifier.journalSpatial Statistics
dc.contributor.institutionDepartment of Mathematical Sciences, Binghamton University, State University of New York, Binghamton, NY 13902, USA
kaust.personGenton, Marc G.
dc.date.published-online2016-09-21
dc.date.published-print2016-11


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