Estimating the tail dependence function of an elliptical distribution

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Semi‐Parametric Models for the Multivariate Tail Dependence Function – the Asymptotically Dependent Case (2008, background): “Therefore, by assuming that the observations have the same distribution as an elliptical random vector Z defined in (2) and P(G > ·)∈RV− for some > 0, Klüppelberg et al. (2007) propose to estimate the tail dependence function via (3) and show that this new estimator is better than the empirical…”
Extreme-value copulas (2009, background): “See for instance [5, 13, 49, 24, 59, 60, 61, 63] for some (semi-)parametric approaches and [1, 6, 23, 22, 25, 81] for some nonparametric ones.”