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• W3100774176 abstract "Let $X_{i,n},nin mathbb{N},1leq ileq n$, be a triangular array of independent $mathbb{R}^d$-valued Gaussian random vectors with correlation matrices $Sigma_{i,n}$. We give necessary conditions under which the row-wise maxima converge to some max-stable distribution which generalizes the class of H{u}sler-Reiss distributions. In the bivariate case, the conditions will also be sufficient. Using these results, new models for bivariate extremes are derived explicitly. Moreover, we define a new class of stationary, max-stable processes as max-mixtures of Brown-Resnick processes. As an application, we show that these processes realize a large set of extremal correlation functions, a natural dependence measure for max-stable processes. This set includes all functions $psi(sqrt{gamma(h)}),hin mathbb{R}^d$, where $psi$ is a completely monotone function and $gamma$ is an arbitrary variogram." @default.
• W3100774176 created "2020-11-23" @default.
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• W3100774176 date "2015-02-01" @default.
• W3100774176 modified "2023-09-28" @default.
• W3100774176 title "Maxima of independent, non-identically distributed Gaussian vectors" @default.
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• W3100774176 doi "https://doi.org/10.3150/13-bej560" @default.
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