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A measure of primal importance for capturing the serial dependence of astationary time series at extreme levels is provided by the limiting clustersize distribution. New estimators based on a blocks declustering scheme areproposed and analyzed both theoretically and by means of a large-scalesimulation study. A sliding blocks version of the estimators is shown tooutperform a disjoint blocks version. In contrast to some competitors from theliterature, the estimators only depend on one unknown parameter to be chosen bythe statistician.

Statistical analysis for stationary time series at extreme levels: new estimators for the limiting cluster size distribution