Natalia Nolde

From geometry of the limit set to extremal dependence properties of light-tailed distributions

Sample clouds of multivariate data points from light-tailed distributions can often be scaled to converge onto a deterministic set as the sample size tends to infinity. It turns out that the shape of this limit set can be related to a number of extremal dependence properties of the underlying distribution. In this talk, I will present several simple relations, and illustrate how they can be used to replace frequently cumbersome or intractable analytical computations.