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The realization problem for tail correlation functions

机译:尾部相关函数的实现问题

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For a stochastic process {X (t) } (taT) with identical one-dimensional margins and upper endpoint tau (up) its tail correlation function (TCF) is defined through . It is a popular bivariate summary measure that has been frequently used in the literature in order to assess tail dependence. In this article, we study its realization problem. We show that the set of all TCFs on TxT coincides with the set of TCFs stemming from a subclass of max-stable processes and can be completely characterized by a system of affine inequalities. Basic closure properties of the set of TCFs and regularity implications of the continuity of chi are derived. If T is finite, the set of TCFs on TxT forms a convex polytope of matrices. Several general results reveal its complex geometric structure. Up to a reduced system of necessary and sufficient conditions for being a TCF is determined. None of these conditions will become obsolete as grows.
机译:对于具有相同一维边界和上端点tau(上)的随机过程{X(t)}(taT),其尾部相关函数(TCF)通过定义。它是一种流行的双变量汇总度量,在文献中经常使用它来评估尾巴依赖性。在本文中,我们研究其实现问题。我们显示,TxT上所有TCF的集合与源自最大稳定过程的子类的TCF的集合一致,并且可以由仿射不等式系统完全表征。推导出TCF集合的基本封闭性质以及chi连续性的规律性含义。如果T是有限的,则TxT上的TCF集会形成矩阵的凸多面体。几项一般结果揭示了其复杂的几何结构。确定直至成为TCF的必要条件和充分条件的简化系统。随着条件的增长,这些条件都不会过时。

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