Tukey max-stable processes for spatial extremes

Ganggang Xu; Marc G. Genton

doi:10.1016/j.spasta.2016.09.002

Tukey max-stable processes for spatial extremes

Ganggang Xu, Marc G. Genton

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12 Scopus citations

Abstract

We 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.

Original language	English (US)
Pages (from-to)	431-443
Number of pages	13
Journal	Spatial Statistics
Volume	18
DOIs	https://doi.org/10.1016/j.spasta.2016.09.002
State	Published - Sep 21 2016

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10.1016/j.spasta.2016.09.002

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title = "Tukey max-stable processes for spatial extremes",

abstract = "We 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. {\textcopyright} 2016 Elsevier B.V.",

author = "Ganggang Xu and Genton, {Marc G.}",

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AU - Genton, Marc G.

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Y1 - 2016/9/21

N2 - We 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.

AB - We 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.

UR - http://hdl.handle.net/10754/622346

UR - http://www.sciencedirect.com/science/article/pii/S2211675316300574

UR - http://www.scopus.com/inward/record.url?scp=84994400060&partnerID=8YFLogxK

U2 - 10.1016/j.spasta.2016.09.002

DO - 10.1016/j.spasta.2016.09.002

M3 - Article

SN - 2211-6753

VL - 18

SP - 431

EP - 443

JO - Spatial Statistics

JF - Spatial Statistics

ER -

Tukey max-stable processes for spatial extremes

Abstract

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