IDEAS home Printed from https://ideas.repec.org/a/spr/testjl/v20y2011i1p138-162.html
   My bibliography  Save this article

A weighted mean excess function approach to the estimation of Weibull-type tails

Author

Listed:
  • Yuri Goegebeur
  • Armelle Guillou

Abstract

No abstract is available for this item.

Suggested Citation

  • Yuri Goegebeur & Armelle Guillou, 2011. "A weighted mean excess function approach to the estimation of Weibull-type tails," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(1), pages 138-162, May.
  • Handle: RePEc:spr:testjl:v:20:y:2011:i:1:p:138-162
    DOI: 10.1007/s11749-010-0190-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11749-010-0190-6
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11749-010-0190-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jean Diebolt & Laurent Gardes & Stéphane Girard & Armelle Guillou, 2008. "Bias-reduced estimators of the Weibull tail-coefficient," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(2), pages 311-331, August.
    2. Holger Drees, 1998. "On Smooth Statistical Tail Functionals," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 25(1), pages 187-210, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yuri Goegebeur & Armelle Guillou & Théo Rietsch, 2015. "Robust conditional Weibull-type estimation," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(3), pages 479-514, June.

    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. Igor Fedotenkov, 2020. "A Review of More than One Hundred Pareto-Tail Index Estimators," Statistica, Department of Statistics, University of Bologna, vol. 80(3), pages 245-299.
    2. Dierckx, Goedele & Goegebeur, Yuri & Guillou, Armelle, 2013. "An asymptotically unbiased minimum density power divergence estimator for the Pareto-tail index," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 70-86.
    3. Gardes, Laurent & Girard, Stéphane, 2016. "On the estimation of the functional Weibull tail-coefficient," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 29-45.
    4. Daouia, Abdelaati & Girard, Stéphane & Stupfler, Gilles, 2018. "Tail expectile process and risk assessment," TSE Working Papers 18-944, Toulouse School of Economics (TSE).
    5. Wager, Stefan, 2014. "Subsampling extremes: From block maxima to smooth tail estimation," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 335-353.
    6. de Haan, Laurens & Canto e Castro, Luisa, 2006. "A class of distribution functions with less bias in extreme value estimation," Statistics & Probability Letters, Elsevier, vol. 76(15), pages 1617-1624, September.
    7. Beirlant, Jan & Escobar-Bach, Mikael & Goegebeur, Yuri & Guillou, Armelle, 2016. "Bias-corrected estimation of stable tail dependence function," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 453-466.
    8. M. Ivette Gomes & Armelle Guillou, 2015. "Extreme Value Theory and Statistics of Univariate Extremes: A Review," International Statistical Review, International Statistical Institute, vol. 83(2), pages 263-292, August.
    9. Neves, Cláudia & Pereira, António, 2010. "Detecting finiteness in the right endpoint of light-tailed distributions," Statistics & Probability Letters, Elsevier, vol. 80(5-6), pages 437-444, March.
    10. Frederico Caeiro & M. Gomes, 2009. "Semi-parametric second-order reduced-bias high quantile estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(2), pages 392-413, August.
    11. Tang, Qihe & Yang, Fan, 2014. "Extreme value analysis of the Haezendonck–Goovaerts risk measure with a general Young function," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 311-320.
    12. Jan Beirlant & John H. J. Einmahl, 2010. "Asymptotics for the Hirsch Index," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(3), pages 355-364, September.
    13. Jürg Hüsler & Deyuan Li, 2008. "Weak Convergence of the Empirical Mean Excess Process with Application to Estimate the Negative Tail Index," Methodology and Computing in Applied Probability, Springer, vol. 10(4), pages 577-593, December.
    14. Pan, Xiaoqing & Leng, Xuan & Hu, Taizhong, 2013. "The second-order version of Karamata’s theorem with applications," Statistics & Probability Letters, Elsevier, vol. 83(5), pages 1397-1403.
    15. Yongcheng Qi, 2010. "On the tail index of a heavy tailed distribution," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(2), pages 277-298, April.
    16. Jo~ao Nicolau & Paulo M. M. Rodrigues, 2024. "A simple but powerful tail index regression," Papers 2409.13531, arXiv.org.
    17. Cuntz, A. & Haeusler, E. & Segers, J.J.J., 2003. "Edgeworth Expansions for the Distribution Function of the Hill Estimator," Other publications TiSEM 345501c7-c622-4b04-8d27-9, Tilburg University, School of Economics and Management.
    18. Matthys, Gunther & Delafosse, Emmanuel & Guillou, Armelle & Beirlant, Jan, 2004. "Estimating catastrophic quantile levels for heavy-tailed distributions," Insurance: Mathematics and Economics, Elsevier, vol. 34(3), pages 517-537, June.
    19. Bucher, Axel & Segers, Johan, 2015. "Maximum likelihood estimation for the Frechet distribution based on block maxima extracted from a time series," LIDAM Discussion Papers ISBA 2015023, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    20. Chiapino, Mael & Sabourin, Anne & Segers, Johan, 2018. "Identifying groups of variables with the potential of being large simultaneously," LIDAM Discussion Papers ISBA 2018006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    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:spr:testjl:v:20:y:2011:i:1:p:138-162. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.