Inference for clusters of extreme values
Address for correspondence: Christopher A. T. Ferro, Department of Meteorology, University of Reading, Earley Gate, PO Box 243, Reading, RG6 6BB, UK.
E‐mail: c.a.t.ferro@reading.ac.uk
Abstract
Summary. Inference for clusters of extreme values of a time series typically requires the identification of independent clusters of exceedances over a high threshold. The choice of declustering scheme often has a significant effect on estimates of cluster characteristics. We propose an automatic declustering scheme that is justified by an asymptotic result for the times between threshold exceedances. The scheme relies on the extremal index, which we show may be estimated before declustering, and supports a bootstrap procedure for assessing the variability of estimates.
Citing Literature
Number of times cited according to CrossRef: 158
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