B1894
Title: Joint asymptotic behavior of maxima over subsets of concomitants in the extremal dependence framework
Authors: Amir Khorrami Chokami - University of Turin (Italy) [presenting]
Marie Kratz - ESSEC Business School, CREAR (France)
Abstract: The study of concomitants has recently met a renewed interest due to its applications in selection procedures. For instance, concomitants are used in ranked-set sampling, to achieve efficiency and reduce cost when compared to simple random sampling. In parallel, the search for new methods to provide a rich description of extremal dependence among multiple time series has rapidly grown, due also to its numerous practical implications and the lack of suitable models to assess it. The aim is to investigate extremal dependence when choosing the concomitants approach. We show how the extremal dependence of a vector $(X, Y)$ impacts the asymptotic behavior of the maxima over subsets of concomitants. Discussing the various conditions and results, we point out the fundamental role played by the marginal distributions of $X$ and $Y$.
