标题： 来自偏斜对称族的极值相依性模型 显示英文标题

标题： Models for extremal dependence derived from skew-symmetric families

摘要： 斜对称分布族，如偏斜正态分布和偏斜$t$分布，代表了正态分布和$t$分布的超集，并且它们展示了更丰富的极值行为类。 通过定义一个非平稳的偏斜正态过程，该过程允许正定的非平稳协方差函数的简单处理，我们推导出一个新的最大稳定过程——极值偏斜$t$过程。 这个过程是包括非平稳过程的超集，其中包括平稳的极值$t$过程。 我们提供了极值偏斜$t$过程的谱表示及其相应的角密度，并展示了其实用实现方法（包含支持信息）。 显示英文摘要

摘要： 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 (Includes Supporting Information).