Speaker: Adam Butler (BIOSS)
Extreme value theory (EVT) is concerned with drawing inferences about the statistical properties of rare events, and the univariate version of EVT is widely used as a basis for risk assessment within disciplines such as hydrology, climatology and finance. Multivariate EVT describes the relationship between the extremes of different processes – or between the extremes of the same process at multiple locations or timepoints – and is substantially more challenging from both a theoretical and practical perspective.
In this talk I will introduce the basic concepts of EVT and outline some of the key statistical ideas that are involved in studying dependence between variables at extreme levels. I will present some recent research in this area on quantifying extremal dependence within Markov chains, and will give an overview of current research on the application of Reversible Jump MCMC to multivariate extreme value models.