摘要翻译：
本文统一和推广了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，无条件分布和条件分布都是EV，所有的低维边际和极大值都属于这类。这导致了理解、分析和预测的实质性经济。模型的一种解释是EV分布的尺寸混合，其中混合是正稳定分布。第二种解释是指数稳定的位置混合（对于Gumbel）或功率稳定的尺度混合（对于非Gumbel EV分布）。第三种解释是通过具有正稳定强度的峰值超过阈值模型。混合变量被用作建模工具，并用于更好地理解和模型检查。我们研究方差模型组件的极值相似，以及新的时间序列、空间和连续参数极值模型。结果被应用于点蚀调查的数据。
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英文标题：
《Models for dependent extremes using stable mixtures》
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作者：
Anne-Laure Foug\`eres (MODAL'X), John P. Nolan, Holger Rootz\'en
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最新提交年份：
2007
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分类信息：

一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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一级分类：Mathematics        数学
二级分类：Statistics Theory        统计理论
分类描述：Applied, computational and theoretical statistics: e.g. statistical inference, regression, time series, multivariate analysis, data analysis, Markov chain Monte Carlo, design of experiments, case studies
应用统计、计算统计和理论统计：例如统计推断、回归、时间序列、多元分析、数据分析、马尔可夫链蒙特卡罗、实验设计、案例研究
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一级分类：Statistics        统计学
二级分类：Statistics Theory        统计理论
分类描述：stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近，贝叶斯推论，决策理论，估计，基础，推论，检验。
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英文摘要：
  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.
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PDF链接：
https://arxiv.org/pdf/711.2345