ABSTRACT
Abstract An overview of existing nonparametric tests of extreme-value dependence is presented. Given an i.i.d. sample of random vectors from a continuous distribution, such tests aim at assessing whether the underlying unknown copula is of the extremevalue type or not. The existing approaches available in the literature are summarized according to how departure from extreme-value dependence is assessed. Related statistical procedures useful when modeling data with this type of dependence are briefly described next. Two illustrations on real datasets are then carried out using some of the statistical procedures under consideration implemented in the R package copula. Finally, the related problem of testing the maximum domain of attraction condition is discussed.
