Probability and Statistics Seminar   RSS

Planned sessions

14/07/2021, 13:00 — 14:00 Europe/Lisbon — Instituto Superior Técnico
, Department of Statistical Science, University College London

Extreme value threshold selection and uncertainty

A common form of extreme value modelling involves modelling excesses of a threshold by a generalised Pareto (GP) distribution. The GP model arises by considering the possible limiting distributions of excesses as the threshold increased. Selecting too low a threshold leads to bias from model misspecification; raising the threshold increases the variance of estimators: a bias-variance trade-off. Some threshold selection methods do not address this trade-off directly, but rather aim to select the lowest threshold above which the GP model is judged to hold approximately. We use Bayesian cross-validation to address the trade-off by comparing thresholds based on predictive ability at extreme levels. Extremal inferences can be sensitive to the choice of a single threshold. We use Bayesian model averaging to combine inferences from many thresholds, thereby reducing sensitivity to the choice of a single threshold. The methodology is illustrated using significant wave height datasets from the North Sea and from the Gulf of Mexico.

Joint seminar CEMAT and CEAUL

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