标题： 依赖极值的稳定混合模型 显示英文标题

标题： Models for dependent extremes using stable mixtures

摘要： 本文统一并扩展了Hougaard、Crowder和Tawn研究的一类多元极值（EV）模型的结果。在这些模型中，无论是无条件分布还是条件分布都是极值分布，并且所有低维边缘分布和极大值都属于此类。这带来了理解、分析和预测方面的重大节约。这些模型的一种解释是作为极值分布的大小混合模型，其中混合由正稳定分布完成。第二种解释是作为Gumbel分布的指数稳定位置混合模型，或者是非Gumbel极值分布的幂稳定尺度混合模型。第三种解释是通过具有正稳定强度的阈值峰值模型。混合变量被用作建模工具以及用于更好地理解和模型检验。我们研究了方差分量模型的极值类比，以及新的时间序列、空间和连续参数极值模型。结果应用于坑蚀调查数据。 显示英文摘要

摘要： This paper unifies and extends results on a class of multivariate Extreme Value (EV) models studied by Hougaard, Crowder, and Tawn. In these models both unconditional and conditional distributions are EV, and all lower-dimensional marginals and maxima belong to the class. This leads to substantial economies of understanding, analysis and prediction. One interpretation of the models is as size mixtures of EV distributions, where the mixing is by positive stable distributions. A second interpretation is as exponential-stable location mixtures (for Gumbel) or as power-stable scale mixtures (for non-Gumbel EV distributions). A third interpretation is through a Peaks over Thresholds model with a positive stable intensity. The mixing variables are used as a modeling tool and for better understanding and model checking. We study extreme value analogues of components of variance models, and new time series, spatial, and continuous parameter models for extreme values. The results are applied to data from a pitting corrosion investigation.