摘要翻译：
本文讨论了边际指数分布的到达时间之间的依赖关系，如金融建模中的违约时间或可靠性理论中的故障间时间。我们探讨了依赖关系和在长时间间隔内对最终多元存活率进行抽样的可能性之间的关系，作为局部多元存活率沿着总时间间隔的一个划分的迭代序列。我们发现，在一种与生存时间系词有关的多元记忆缺失形式下，这是可能的。这一性质定义了一个“自链Copula”，并证明了这与极值copulas刻画是一致的。Gumbel-Hougaard copula和Marshall-Olkin copula满足了自链条件，Gumbel-Hougaard copula是阿基米德族中自链copula的一个完整刻画。该结果对于一致的单步和多步模拟多变量到达时间具有重要的实际意义，这种方法不会通过迭代破坏依赖关系，就像不一致迭代高斯Copula时发生的那样。
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英文标题：
《Consistent single- and multi-step sampling of multivariate arrival
  times: A characterization of self-chaining copulas》
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作者：
Damiano Brigo, Kyriakos Chourdakis
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最新提交年份：
2012
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分类信息：

一级分类：Mathematics        数学
二级分类：Probability        概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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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：Quantitative Finance        数量金融学
二级分类：Pricing of Securities        证券定价
分类描述：Valuation and hedging of financial securities, their derivatives, and structured products
金融证券及其衍生产品和结构化产品的估值和套期保值
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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 deals with dependence across marginally exponentially distributed arrival times, such as default times in financial modeling or inter-failure times in reliability theory. We explore the relationship between dependence and the possibility to sample final multivariate survival in a long time-interval as a sequence of iterations of local multivariate survivals along a partition of the total time interval. We find that this is possible under a form of multivariate lack of memory that is linked to a property of the survival times copula. This property defines a "self-chaining-copula", and we show that this coincides with the extreme value copulas characterization. The self-chaining condition is satisfied by the Gumbel-Hougaard copula, a full characterization of self chaining copulas in the Archimedean family, and by the Marshall-Olkin copula. The result has important practical implications for consistent single-step and multi-step simulation of multivariate arrival times in a way that does not destroy dependency through iterations, as happens when inconsistently iterating a Gaussian copula.
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PDF链接：
https://arxiv.org/pdf/1204.2090