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

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  • Bücher, Axel
  • Jennessen, Tobias

Abstract

The serial dependence of a stationary time series at extreme levels may be captured by the limiting cluster size distribution. New estimators based on a blocks declustering scheme are proposed and analyzed both theoretically and by means of a large-scale simulation study. A sliding blocks version of the estimators is shown to outperform a disjoint blocks version. In contrast to some competitors from the literature, the estimators only depend on one tuning parameter to be chosen by the statistician.

Suggested Citation

  • Bücher, Axel & Jennessen, Tobias, 2022. "Statistical analysis for stationary time series at extreme levels: New estimators for the limiting cluster size distribution," Stochastic Processes and their Applications, Elsevier, vol. 149(C), pages 75-106.
    • Handle: RePEc:eee:spapps:v:149:y:2022:i:c:p:75-106
    DOI: 10.1016/j.spa.2022.03.004
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    References listed on IDEAS

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