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Bivariate Distributions with Given Extreme Value Attractor

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  • Capéraà, Philippe
  • Fougères, Anne-Laure
  • Genest, Christian

Abstract

A new class of bivariate distributions is introduced and studied, which encompasses Archimedean copulas and extreme value distributions as special cases. Its dependence structure is described, its maximum and minimum attractors are determined, and an algorithm is given for generating observations from any member of this class. It is also shown how it is possible to construct distributions in this family with a predetermined extreme value attractor. This construction is used to study via simulation the small-sample behavior of a bivariate threshold method suggested by H. Joe, R. L. Smith, and I. Weissman (1992, J. Roy. Statist. Soc. Ser. B54, 171-183) for estimating the joint distribution of extremes of two random variates.

Suggested Citation

  • Capéraà, Philippe & Fougères, Anne-Laure & Genest, Christian, 2000. "Bivariate Distributions with Given Extreme Value Attractor," Journal of Multivariate Analysis, Elsevier, vol. 72(1), pages 30-49, January.
  • Handle: RePEc:eee:jmvana:v:72:y:2000:i:1:p:30-49
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    References listed on IDEAS

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    1. Deheuvels, Paul, 1991. "On the limiting behavior of the Pickands estimator for bivariate extreme-value distributions," Statistics & Probability Letters, Elsevier, vol. 12(5), pages 429-439, November.
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    Citations

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    Cited by:

    1. Keef, Caroline & Papastathopoulos, Ioannis & Tawn, Jonathan A., 2013. "Estimation of the conditional distribution of a multivariate variable given that one of its components is large: Additional constraints for the Heffernan and Tawn model," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 396-404.
    2. Charpentier, A. & Fougères, A.-L. & Genest, C. & Nešlehová, J.G., 2014. "Multivariate Archimax copulas," Journal of Multivariate Analysis, Elsevier, vol. 126(C), pages 118-136.
    3. repec:dau:papers:123456789/3346 is not listed on IDEAS
    4. Genest, C. & Werker, B.J.M., 2001. "Conditions for the asymptotic semiparametric efficiency of an omnibus estimator of dependence parameters in copula models," Other publications TiSEM b733c3f4-38d2-49aa-a2c7-4, Tilburg University, School of Economics and Management.
    5. Sabrina Mulinacci, 2015. "Archimedean-based Marshall-Olkin Distributions and Related Copula Functions," Papers 1502.01912, arXiv.org.
    6. Ferreira, Helena, 2012. "Multivariate maxima of moving multivariate maxima," Statistics & Probability Letters, Elsevier, vol. 82(8), pages 1489-1496.
    7. repec:spr:stmapp:v:26:y:2017:i:3:d:10.1007_s10260-016-0375-6 is not listed on IDEAS
    8. A. Colin Cameron & Tong Li & Pravin K. Trivedi & David M. Zimmer, 2004. "Modelling the differences in counted outcomes using bivariate copula models with application to mismeasured counts," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 566-584, December.
    9. Gardes, Laurent & Girard, Stéphane, 2015. "Nonparametric estimation of the conditional tail copula," Journal of Multivariate Analysis, Elsevier, vol. 137(C), pages 1-16.
    10. Umberto Cherubini & Sabrina Mulinacci, 2015. "Systemic Risk with Exchangeable Contagion: Application to the European Banking System," Papers 1502.01918, arXiv.org.
    11. Di Bernardino Elena & Rullière Didier, 2016. "On an asymmetric extension of multivariate Archimedean copulas based on quadratic form," Dependence Modeling, De Gruyter Open, vol. 4(1), pages 1-20, December.
    12. Elena Di Bernardino & Didier Rullière, 2016. "On an asymmetric extension of multivariate Archimedean copulas based on quadratic form," Working Papers hal-01147778, HAL.
    13. Cuculescu, Ioan & Theodorescu, Radu, 2003. "Are copulas unimodal?," Journal of Multivariate Analysis, Elsevier, vol. 86(1), pages 48-71, July.
    14. Mai, Jan-Frederik & Scherer, Matthias, 2012. "H-extendible copulas," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 151-160.
    15. Joe, Harry & Ma, Chunsheng, 2000. "Multivariate Survival Functions with a Min-Stable Property," Journal of Multivariate Analysis, Elsevier, vol. 75(1), pages 13-35, October.
    16. Fung, Thomas & Seneta, Eugene, 2014. "Convergence rate to a lower tail dependence coefficient of a skew-t distribution," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 62-72.
    17. Gabriel GAIDUCHEVICI, 2015. "A Method For Systemic Risk Estimation Based On Cds Indices," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 15, pages 103-124, June.
    18. Charpentier, Arthur & Segers, Johan, 2009. "Tails of multivariate Archimedean copulas," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1521-1537, August.
    19. Frahm, Gabriel & Junker, Markus & Schmidt, Rafael, 2005. "Estimating the tail-dependence coefficient: Properties and pitfalls," Insurance: Mathematics and Economics, Elsevier, vol. 37(1), pages 80-100, August.
    20. Quessy, Jean-François & Bahraoui, Tarik, 2014. "Weak convergence of empirical and bootstrapped C-power processes and application to copula goodness-of-fit," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 16-36.
    21. Nikoloulopoulos, Aristidis K. & Karlis, Dimitris, 2008. "Copula model evaluation based on parametric bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3342-3353, March.
    22. Durante, Fabrizio & Jaworski, Piotr & Mesiar, Radko, 2011. "Invariant dependence structures and Archimedean copulas," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1995-2003.
    23. German Bernhart & Marcos Escobar Anel & Jan-Frederik Mai & Matthias Scherer, 2013. "Default models based on scale mixtures of Marshall-Olkin copulas: properties and applications," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(2), pages 179-203, February.
    24. Wysocki, Włodzimierz, 2013. "When a copula is archimax," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 37-45.
    25. Genest, Christian & Rivest, Louis-Paul, 2001. "On the multivariate probability integral transformation," Statistics & Probability Letters, Elsevier, vol. 53(4), pages 391-399, July.

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