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Models for Extremal Dependence Derived from Skew‐symmetric Families
Authors:Boris Beranger  Simone A. Padoan  Scott A. Sisson
Affiliation:1. School of Mathematics and StatisticsUniversity of New South Wales;2. Department of Decision SciencesBocconi University
Abstract:Skew‐symmetric families of distributions such as the skew‐normal and skew‐t represent supersets of the normal and t distributions, and they exhibit richer classes of extremal behaviour. By defining a non‐stationary skew‐normal process, which allows the easy handling of positive definite, non‐stationary covariance functions, we derive a new family of max‐stable processes – the extremal skew‐t process. This process is a superset of non‐stationary processes that include the stationary extremal‐t processes. We provide the spectral representation and the resulting angular densities of the extremal skew‐t process and illustrate its practical implementation.
Keywords:angular density   asymptotic independence   extremal coefficient   extreme values   max‐stable distribution   non‐central extended skew‐t distribution   non‐stationarity   skew‐normal distribution   skew‐normal process   skew‐t distribution
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