Regional Modelling of Extreme Storms Via Max-Stable Processes

Stuart Coles

108 citations0/0 files storedJournal of the Royal Statistical Society Series B (Statistical Methodology)

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Probability and Risk Models Climate variability and models Point processes and geometric inequalities

Abstract

SUMMARY Asymptotic models for extremes of random processes often form the basis for estimating the extremal behaviour of environmental phenomena. Most such phenomena have a spatial dimension, and the aim of this paper is to develop a procedure for modelling in continuous space the spatial dependence within extreme events. A principal objective in the analysis—as with other current research on extremes—is to base inference on as much of the available data as possible. The modelling procedures are justified on simulated data and subsequently applied to a series of rainfall data.

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References

1987Extreme Values, Regular Variation and Point Processes 1990The Asymptotic Theory of Extreme Order Statistics 1990Models for Exceedances Over High Thresholds 1989Extreme Value Analysis of Environmental Time Series: An Application to Trend Detection in Ground-Level Ozone 1988Bivariate Extreme Value Theory: Models and Estimation 1991Modelling Extreme Multivariate Events 1984A Spectral Representation for Max-stable Processes 1977Limit theory for multivariate sample extremes

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2010Continuous Spatial Process Models for Spatial Extreme Values 2006Spatial extremes: Models for the stationary case 2009Continuous Spatial Process Models for Spatial Extreme Values 2016Exact simulation of max-stable processes 2002Inequalities for the Extremal Coefficients of Multivariate Extreme Value Distributions 2013Max-stable processes for modeling extremes observed in space and time

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