Multivariate max-stable spatial processes

Marc G. Genton, S. A. Padoan, H. Sang

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Max-stable processes allow the spatial dependence of extremes to be modelled and quantified, so they are widely adopted in applications. For a better understanding of extremes, it may be useful to study several variables simultaneously. To this end, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. We define a Poisson process construction and introduce multivariate versions of the Smith Gaussian extreme-value, the Schlather extremal-Gaussian and extremal-t, and the Brown–Resnick models. We develop inference for the models based on composite likelihoods. We present results of Monte Carlo simulations and an application to daily maximum wind speed and wind gust.
Original languageEnglish (US)
Pages (from-to)215-230
Number of pages16
JournalBiometrika
Volume102
Issue number1
DOIs
StatePublished - Feb 11 2015

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