IDEAS home Printed from https://ideas.repec.org/p/tiu/tiutis/0b2c1bfa-d609-494a-8929-8091049de1a7.html
   My bibliography  Save this paper

Weighted Approximations of Tail Copula Processes with Application to Testing the Multivariate Extreme Value Condition

Author

Listed:
  • Einmahl, J.H.J.

    (Tilburg University, School of Economics and Management)

  • de Haan, L.F.M.

    (Tilburg University, School of Economics and Management)

  • Li, D.

Abstract

No abstract is available for this item.

Suggested Citation

  • Einmahl, J.H.J. & de Haan, L.F.M. & Li, D., 2004. "Weighted Approximations of Tail Copula Processes with Application to Testing the Multivariate Extreme Value Condition," Other publications TiSEM 0b2c1bfa-d609-494a-8929-8, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:0b2c1bfa-d609-494a-8929-8091049de1a7
    as

    Download full text from publisher

    File URL: https://pure.uvt.nl/ws/portalfiles/portal/628521/71.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Einmahl, J.H.J. & de Haan, L.F.M. & Piterbarg, V.I., 2001. "Nonparametric estimation of the spectral measure of an extreme value distribution," Other publications TiSEM c3485b9b-a0bd-456f-9baa-0, Tilburg University, School of Economics and Management.
    3. Einmahl, J.H.J., 1992. "Limit theorems for tail processes with application to intermediate quantile estimation," Other publications TiSEM 063e51b0-445d-4764-96a2-4, Tilburg University, School of Economics and Management.
    4. Schlather, Martin, 2001. "Examples for the coefficient of tail dependence and the domain of attraction of a bivariate extreme value distribution," Statistics & Probability Letters, Elsevier, vol. 53(3), pages 325-329, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Einmahl, J.H.J. & de Haan, L.F.M. & Li, D., 2006. "Weighted approximations of tail copula processes with applications to testing the bivariate extreme value condition," Other publications TiSEM 18b65ac3-ba79-4bff-ad53-2, Tilburg University, School of Economics and Management.
    2. Einmahl, J.H.J. & de Haan, L.F.M. & Piterbarg, V.I., 2001. "Nonparametric estimation of the spectral measure of an extreme value distribution," Other publications TiSEM c3485b9b-a0bd-456f-9baa-0, Tilburg University, School of Economics and Management.
    3. Di Bernardino, Elena & Maume-Deschamps, Véronique & Prieur, Clémentine, 2013. "Estimating a bivariate tail: A copula based approach," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 81-100.
    4. Ahmed, Hanan, 2022. "Extreme value statistics using related variables," Other publications TiSEM 246f0f13-701c-4c0d-8e09-e, Tilburg University, School of Economics and Management.
    5. Einmahl, J.H.J. & Segers, J.J.J., 2008. "Maximum Empirical Likelihood Estimation of the Spectral Measure of an Extreme Value Distribution," Discussion Paper 2008-42, Tilburg University, Center for Economic Research.
    6. Khader Khadraoui & Pierre Ribereau, 2019. "Bayesian Inference with M-splines on Spectral Measure of Bivariate Extremes," Methodology and Computing in Applied Probability, Springer, vol. 21(3), pages 765-788, September.
    7. Goix, Nicolas & Sabourin, Anne & Clémençon, Stephan, 2017. "Sparse representation of multivariate extremes with applications to anomaly detection," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 12-31.
    8. Kiriliouk, Anna & Segers, Johan & Warchol, Michal, 2014. "Nonparametric estimation of extremal dependence," LIDAM Discussion Papers ISBA 2014044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Hu, Shuang & Peng, Zuoxiang & Segers, Johan, 2022. "Modelling multivariate extreme value distributions via Markov trees," LIDAM Discussion Papers ISBA 2022021, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    10. Fils-Villetard, A. & Guillou, A. & Segers, J., 2005. "Projection Estimates of Constrained Functional Parameters," Discussion Paper 2005-111, Tilburg University, Center for Economic Research.
    11. Zhang, Dabao & Wells, Martin T. & Peng, Liang, 2008. "Nonparametric estimation of the dependence function for a multivariate extreme value distribution," Journal of Multivariate Analysis, Elsevier, vol. 99(4), pages 577-588, April.
    12. 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.
    13. Guzmics Sándor & Pflug Georg Ch., 2020. "A new extreme value copula and new families of univariate distributions based on Freund’s exponential model," Dependence Modeling, De Gruyter, vol. 8(1), pages 330-360, January.
    14. Jochmans, Koen & Henry, Marc & Salanié, Bernard, 2017. "Inference On Two-Component Mixtures Under Tail Restrictions," Econometric Theory, Cambridge University Press, vol. 33(3), pages 610-635, June.
    15. repec:spo:wpmain:info:hdl:2441/f6h8764enu2lskk9p2m96cphi is not listed on IDEAS
    16. Estate Khmaladze & Wolfgang Weil, 2008. "Local empirical processes near boundaries of convex bodies," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(4), pages 813-842, December.
    17. Goegebeur, Yuri & Guillou, Armelle & Qin, Jing, 2024. "Dependent conditional tail expectation for extreme levels," Stochastic Processes and their Applications, Elsevier, vol. 171(C).
    18. Ahmed, Hanan & Einmahl, John, 2018. "Improved Estimation of the Extreme Value Index Using Related Variables," Discussion Paper 2018-025, Tilburg University, Center for Economic Research.
    19. John H. J. Einmahl & Anna Kiriliouk & Andrea Krajina & Johan Segers, 2016. "An M-estimator of spatial tail dependence," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 275-298, January.
    20. Asenova, Stefka & Segers, Johan, 2022. "Extremes of Markov random fields on block graphs," LIDAM Discussion Papers ISBA 2022013, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    21. Kiriliouk, Anna, 2020. "Hypothesis testing for tail dependence parameters on the boundary of the parameter space," Econometrics and Statistics, Elsevier, vol. 16(C), pages 121-135.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tiu:tiutis:0b2c1bfa-d609-494a-8929-8091049de1a7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Richard Broekman (email available below). General contact details of provider: https://www.tilburguniversity.edu/about/schools/economics-and-management/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.