Abstract A new class of hierarchical copulas is introduced based on joint survival functions of multivariate exponential mixture distributions. The key element of this construction is the mixing random vector defined by convolutions associated to a Levy subordinator, and leading to hierarchical copulas with Archimedean within-block copulas and asymmetric between-block pair-copulas. For the specific case of two-level trees, dependence properties of pairs are investigated, and a full estimation procedure is proposed for the tree structure and parameters of the hierarchical copulas. The efficiency of the procedure is illustrated through three simulation examples and a study with two real datasets.

中文翻译：

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具有阿基米德块和不对称块间对的分层联结

摘要 基于多元指数混合分布的联合生存函数，引入了一类新的分层copula。这种构造的关键元素是混合随机向量，由与 Levy 从属关联的卷积定义，并导致具有阿基米德块内 copula 和不对称块间对 copula 的分层 copula。针对两级树的具体情况，研究了对的依赖属性，并提出了一个完整的估计程序，用于层次联结的树结构和参数。该程序的效率通过三个模拟示例和对两个真实数据集的研究来说明。