Extreme value estimation using the likelihood-weighted method

Wada, R. and Waseda, T. and Jonathan, P. (2016) Extreme value estimation using the likelihood-weighted method. Ocean Engineering, 124. pp. 241-251. ISSN 0029-8018

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Abstract

This paper proposes a practical approach to extreme value estimation for small samples of observations with truncated values, or high measurement uncertainty, facilitating reasonable estimation of epistemic uncertainty. The approach, called the likelihood-weighted method (LWM), involves Bayesian inference incorporating group likelihood for the generalised Pareto or generalised extreme value distributions and near-uniform prior distributions for parameters. Group likelihood (as opposed to standard likelihood) provides a straightforward mechanism to incorporate measurement error in inference, and adopting flat priors simplifies computation. The method's statistical and computational efficiency are validated by numerical experiment for small samples of size at most 10. Ocean wave applications reveal shortcomings of competitor methods, and advantages of estimating epistemic uncertainty within a Bayesian framework in particular. © 2016 Elsevier Ltd

Item Type:
Journal Article
Journal or Publication Title:
Ocean Engineering
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2200/2212
Subjects:
?? bayesextremegroup likelihoodlikelihood-weighted methoduncertaintybayesian networkscomputational efficiencyinference enginesmeasurement errorsnumerical methodswater wavesweighted methoduncertainty analysisbayesian analysisestimation methodnumerical methodo ??
ID Code:
133042
Deposited By:
Deposited On:
23 Apr 2019 13:30
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 19:19