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Statistics for Tail Processes of Markov Chains

Author

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  • Drees, Holger
  • Segers, Johan
  • Warchol, Michal

Abstract

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Suggested Citation

  • Drees, Holger & Segers, Johan & Warchol, Michal, 2015. "Statistics for Tail Processes of Markov Chains," LIDAM Reprints ISBA 2015023, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  • Handle: RePEc:aiz:louvar:2015023
    Note: In : Extremes : statistical theory and applications in science, engineering and economics, vol. 18, no. 3, p. 369-402 (2015)
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    Cited by:

    1. Segers, Johan & Zhao, Yuwei & Meinguet, Thomas, 2016. "Radial-angular decomposition of regularly varying time series in star-shaped metric spaces," LIDAM Discussion Papers ISBA 2016017, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Davis, Richard & Holger, Drees & Segers, Johan & Warchol, Michal, 2016. "Modeling serial extremal dependence," LIDAM Discussion Papers ISBA 2016016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. 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.
    4. Drees, Holger & Janßen, Anja & Neblung, Sebastian, 2021. "Cluster based inference for extremes of time series," Stochastic Processes and their Applications, Elsevier, vol. 142(C), pages 1-33.
    5. Davis, Richard & Drees, Holger & Segers, Johan & Warchol, Michal, 2018. "Inference on the tail process with application to financial time series modelling," LIDAM Discussion Papers ISBA 2018002, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Durieu, Olivier & Wang, Yizao, 2022. "Phase transition for extremes of a stochastic model with long-range dependence and multiplicative noise," Stochastic Processes and their Applications, Elsevier, vol. 143(C), pages 55-88.
    7. Zhao, Zifeng & Zhang, Zhengjun & Chen, Rong, 2018. "Modeling maxima with autoregressive conditional Fréchet model," Journal of Econometrics, Elsevier, vol. 207(2), pages 325-351.
    8. Buriticá, Gloria & Mikosch, Thomas & Wintenberger, Olivier, 2023. "Large deviations of ℓp-blocks of regularly varying time series and applications to cluster inference," Stochastic Processes and their Applications, Elsevier, vol. 161(C), pages 68-101.

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