The underlying dependence structure between two random variables can be described in manifold ways. This includes the examination of certain dependence properties such as lower tail decreasingness (LTD), stochastic increasingness (SI) or total positivity of order 2, the latter usually considered for a copula (TP2) or (if existent) its density (d-TP2). In the present paper we investigate total positivity of order 2 for a copula's Markov kernel (MK-TP2 for short), a positive dependence property that is stronger than TP2 and SI, weaker than d-TP2 but, unlike d-TP2, is not restricted to absolutely continuous copulas, making it presumably the strongest dependence property defined for any copula (including those with a singular part such as Marshall-Olkin copulas). We examine the MK-TP2 property for different copula families, among them the class of Archimedean copulas and the class of extreme value copulas. In particular we show that, within the class of Archimedean copulas, the dependence properties SI and MK-TP2 are equivalent.
翻译:可以用多种方式描述两个随机变量之间的基本依赖性结构。这包括检查某些依赖性属性,如尾尾部下降(LTD)、肉眼增加(SI)或第2号单项的完全顺势性,后者通常考虑的为(如果存在的话)其密度(d-TP2)。 本文我们调查了Copula的马可夫内核(MK-TP2短)第2号单项的完全假设性,一种比TP2和SI强的正依赖性属性,比d-TP2弱,但与d-TP2不同的是,它并不局限于绝对连续的椰子,因此它可能是为任何椰子(包括马歇尔-奥金椰子等单一部分的椰子)所定义的最强的依赖性属性。我们研究了不同椰子家族的MK-TP2号单项属性,其中包括Archimediane copulas类和极值椰子类。我们特别表明,在Archimedes类中,SI和MK-TP2类的依赖性属性是相等的。