Careful modelling of covariate effects is critical to reliable specification of design criteria. We present a spline based methodology to incorporate spatial, directional, temporal and other covariate effects in extreme value models for environmental variables such as storm severity. For storm peak significant wave height events, the approach uses quantile regression to estimate a suitable extremal threshold, a Poisson process model for the rate of occurrence of threshold exceedances, and a generalised Pareto model for size of threshold. Multidimensional covariate effects are incorporated at each stage using penalised tensor products of B-splines to give smooth model parameter variation as a function of multiple covariates. Optimal smoothing penalties are selected using cross-validation, and model uncertainty is quantified using a bootstrap resampling procedure. The method is applied to estimate return values for a large spatial neighbourhood of locations off the North West Shelf of Australia, incorporating spatial and directional effects.
Modelling Covariate Effects in Extremes of Storm Severity on the Australian North West Shelf
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Randell, D, Wu, Y, Jonathan, P, & Ewans, K. "Modelling Covariate Effects in Extremes of Storm Severity on the Australian North West Shelf." Proceedings of the ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. Volume 2A: Structures, Safety and Reliability. Nantes, France. June 9–14, 2013. V02AT02A019. ASME. https://doi.org/10.1115/OMAE2013-10187
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