Statistical Analysis of Multivariate Extremes

This lecture covers the statistical analysis of multivariate extremes, including extremal limit theorems, point processes, Gaussian processes, Poisson processes, and models for extremes of time series. The instructor explains the estimation of marginal distributions, model fitting, and model assessment. The lecture also explores the estimation of dependence functions and the fitting of space-time models. Various max-stable models are discussed, along with the comparison of observed and simulated values. The lecture emphasizes the importance of pairwise likelihood and the use of information measures for model selection.