Inference for Max-Stable Processes

This lecture covers the inference steps for max-stable processes, including estimation of marginal distributions, model fitting, and model assessment. It introduces the F-madogram as an exploratory tool for extremes and explains the estimation of extremal coefficients. The lecture also discusses the pairwise space-time extremal coefficients and the fitting of Brown-Resnick max-stable rainfall models. Various max-stable models are compared, and the importance of using these models for joint extremal properties is highlighted.