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  • PaperFeb2020

    Accepted author manuscript, 485 KB, PDF document

    Embargo ends: 1/01/50

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Inference for extreme values under threshold-based stopping rules

Research output: Contribution to journalJournal article

Forthcoming
<mark>Journal publication date</mark>10/04/2020
<mark>Journal</mark>Journal of the Royal Statistical Society: Series C (Applied Statistics)
Publication statusAccepted/In press
Original languageEnglish

Abstract

There is a propensity for an extreme value analyses to be conducted as
a consequence of the occurrence of a large flooding event. This timing
of the analysis introduces bias and poor coverage probabilities into the associated risk assessments and leads subsequently to inefficient flood protection schemes. We explore these problems through studying stochastic stopping criteria and propose new likelihood-based inferences
that mitigate against these difficulties. Our methods are illustrated through the analysis of the river Lune, following it experiencing the UK'€™s largest ever measured flow event in 2015. We show that without accounting for this stopping feature there would be substantial over-design in response to the event.