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Empirical tail copulas for functional data


  • Einmahl, John
  • Segers, Johan


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  • Einmahl, John & Segers, Johan, 2020. "Empirical tail copulas for functional data," LIDAM Discussion Papers ISBA 2020004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  • Handle: RePEc:aiz:louvad:2020004

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    1. Einmahl, J.H.J. & Lin, T., 2003. "Asymptotic Normality of Extreme Value Estimators on C[0,1]," Discussion Paper 2003-132, Tilburg University, Center for Economic Research.
    2. Einmahl, John & Kiriliouk, A. & Segers, J.J.J., 2016. "A Continuous Updating Weighted Least Squares Estimator of Tail Dependence in High Dimensions," Other publications TiSEM a3e7350b-4773-4bd8-9c3c-6, Tilburg University, School of Economics and Management.
    3. Einmahl, J.H.J. & Krajina, A. & Segers, J., 2011. "An M-Estimator for Tail Dependence in Arbitrary Dimensions," Discussion Paper 2011-013, Tilburg University, Center for Economic Research.
    4. Rafael Schmidt & Ulrich Stadtmüller, 2006. "Non‐parametric Estimation of Tail Dependence," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 307-335, June.
    5. Clément Dombry & Mathieu Ribatet & Stilian Stoev, 2018. "Probabilities of Concurrent Extremes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(524), pages 1565-1582, October.
    6. Einmahl, J.H.J. & Gantner, M. & Sawitzki, G., 2008. "The Shorth Plot," Discussion Paper 2008-24, Tilburg University, Center for Economic Research.
    7. Peng, Liang & Qi, Yongcheng, 2008. "Bootstrap approximation of tail dependence function," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1807-1824, September.
    8. Chiapino, Mael & Sabourin, Anne & Segers, Johan, 2019. "Identifying groups of variables with the potential of being large simultaneously," ISBA Reprints (ISBA - Institute of Statistics, Biostatistics and Actuarial Sciences) 2019021, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Ressel, Paul, 2013. "Homogeneous distributions—And a spectral representation of classical mean values and stable tail dependence functions," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 246-256.
    10. Hüsler, Jürg & Reiss, Rolf-Dieter, 1989. "Maxima of normal random vectors: Between independence and complete dependence," Statistics & Probability Letters, Elsevier, vol. 7(4), pages 283-286, February.
    11. Drees, Holger & Huang, Xin, 1998. "Best Attainable Rates of Convergence for Estimators of the Stable Tail Dependence Function," Journal of Multivariate Analysis, Elsevier, vol. 64(1), pages 25-47, January.
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