Bayesian Clustering and Dimension Reduction in Multivariate Extremes
نویسندگان
چکیده
The spatial dependence structure of climate extremes may be represented by the class of max-stable distributions. When the domain is very large, describing the spatial dependence between and within subdomains is particularly challenging and requires very flexible, yet interpretable, models. In this work, we use the inherent hierarchical dependence structure of the (max-stable) nested logistic distribution for clustering and dimension reduction in multivariate extremes, taking into account the occurrence times of extreme events. Methods are tested both through a simulation study and by analysing extreme air temperatures at different stations in Switzerland.
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