Functional peaks‐over‐threshold analysis

Peaks‐over‐threshold analysis using the generalised Pareto distribution is widely applied in modelling tails of univariate random variables, but much information may be lost when complex extreme events are studied using univariate results. In this paper, we extend peaks‐over‐threshold analysis to ex...

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Veröffentlicht in:Journal of the Royal Statistical Society. Series B, Statistical methodology Statistical methodology, 2022-09, Vol.84 (4), p.1392-1422
Hauptverfasser: de Fondeville, Raphaël, Davison, Anthony C.
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description Peaks‐over‐threshold analysis using the generalised Pareto distribution is widely applied in modelling tails of univariate random variables, but much information may be lost when complex extreme events are studied using univariate results. In this paper, we extend peaks‐over‐threshold analysis to extremes of functional data. Threshold exceedances defined using a functional r are modelled by the generalised r‐Pareto process, a functional generalisation of the generalised Pareto distribution that covers the three classical regimes for the decay of tail probabilities, and that is the only possible continuous limit for r‐exceedances of a properly rescaled process. We give construction rules, simulation algorithms and inference procedures for generalised r‐Pareto processes, discuss model validation and apply the new methodology to extreme European windstorms and heavy spatial rainfall.
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source Oxford University Press Journals All Titles (1996-Current); Wiley Online Library Journals Frontfile Complete; EBSCOhost Business Source Complete
subjects Algorithms
Extremes
functional regular variation
peaks‐over‐threshold analysis
Rainfall
Random variables
Regression analysis
r‐Pareto process
Simulation
spatial statistics
Statistical methods
Statistics
statistics of extremes
windstorm
title Functional peaks‐over‐threshold analysis
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