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Lookup NU author(s): Dr Lee Fawcett, Dr David WalshawORCiD
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A typical extreme value analysis is often carried out on the basis of simplistic inferential procedures, though the data being analysed may be structurally complex. Here we develop a hierarchical model for hourly gust maximum wind speed data, which attempts to identify site and seasonal effects for the marginal densities of hourly maxima, as well as for the serial dependence at each location. A Gaussian model for the random effects exploits the meteorological structure in the data, enabling increased precision for inferences at individual sites and in individual seasons. The Bayesian framework that is adopted is also exploited to obtain predictive return level estimates at each site, which incorporate uncertainty due to model estimation, as well as the randomness that is inherent in the processes that are involved. © 2006 Royal Statistical Society.
Author(s): Fawcett L, Walshaw D
Publication type: Article
Publication status: Published
Journal: Journal of the Royal Statistical Society. Series C: Applied Statistics
Year: 2006
Volume: 55
Issue: 5
Pages: 631-646
ISSN (print): 0035-9254
ISSN (electronic): 1467-9876
Publisher: Wiley-Blackwell
URL: http://dx.doi.org/10.1111/j.1467-9876.2006.00557.x
DOI: 10.1111/j.1467-9876.2006.00557.x
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