Tail Dependence Comparison of Survival Marshall–Olkin Copulas

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Tail Dependence for Heavy-Tailed Scale Mixtures of Multivariate Distributions (2009, methodology): “In [14] and [15], using the copula method, Li derived explicit expressions of the orthant tail dependence for Marshall–Olkin distributions as well as multivariate extreme value distributions and their scaled mixtures.”
Bivariate Kumaraswamy distribution: properties and a new method to generate bivariate classes (2013, background): “From Theorem 1 given in [27], we obtain that the upper-orthant tail dependence measures for the BVK distribution are γ Ĉ 1 = γ Ĉ 2 = α3/ max{α1 + α3, α2 + α3}.”
Reparameterizing Marshall–Olkin copulas with applications to sampling (2011, methodology): “The precise analytical form of the copula behind the Marshall–Olkin distribution is computed in 8 .”
Extreme value properties of multivariate t copulas (2009, methodology): “Using the formulas of tail dependence parameters for Marshall-Olkin distributions (see, e.g., Li, 2007), we have λ12 = 0, λ13 = 1/4, λ23 = 1/2.”
Copula-Based Measures of Multivariate Association (2010, background): “Other copulas are for example considered in Schmidt [97], Li [71, 72], Joe et al.”
Copula Theory: An Introduction (2010, background): “’s associated with some shock model had its origin in the seminal paper by Marshall and Olkin (see [133]), where the multivariate exponential distribution was considered (see also [121, 122, 147])).”