IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v76y2006i1p10-18.html

On the joint asymptotic behavior of two rank-based estimators of the association parameter in the gamma frailty model

Author

Listed:
  • Genest, Christian
  • Quessy, Jean-François
  • Rémillard, Bruno

Abstract

Rank-based estimators were proposed by Clayton [Clayton D.G., 1978. A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika 65, 141-151.] and Oakes [Oakes, D., 1982. A model for association in bivariate survival data. J. Roy. Statist. Soc. Ser. B 44, 414-422.] for the association parameter in the bivariate gamma frailty model. The joint asymptotic behavior of these estimators is considered here, following a different approach from that used by Oakes [Oakes, D., 1982. A model for association in bivariate survival data. J. Roy. Statist. Soc. Ser. B 44, 414-422; Oakes, D., 1986. Semiparametric inference in a model for association in bivariate survival data. Biometrika 73, 353-361]. This leads to a correction of the formula given by Shih [Shih, J.H. 1998. A goodness-of-fit test for association in a bivariate survival model. Biometrika 85, 189-200.] for the limiting covariance between the two estimators.

Suggested Citation

  • Genest, Christian & Quessy, Jean-François & Rémillard, Bruno, 2006. "On the joint asymptotic behavior of two rank-based estimators of the association parameter in the gamma frailty model," Statistics & Probability Letters, Elsevier, vol. 76(1), pages 10-18, January.
  • Handle: RePEc:eee:stapro:v:76:y:2006:i:1:p:10-18
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(05)00260-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Wenqing He & Jerald F. Lawless, 2003. "Flexible Maximum Likelihood Methods for Bivariate Proportional Hazards Models," Biometrics, The International Biometric Society, vol. 59(4), pages 837-848, December.
    2. Weijing Wang, 2003. "Estimating the association parameter for copula models under dependent censoring," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 257-273, February.
    3. Genest, Christian & Rivest, Louis-Paul, 2001. "On the multivariate probability integral transformation," Statistics & Probability Letters, Elsevier, vol. 53(4), pages 391-399, July.
    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. Daniel Berg & Jean‐François Quessy, 2009. "Local Power Analyses of Goodness‐of‐fit Tests for Copulas," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(3), pages 389-412, September.
    2. Nasri, Bouchra R., 2022. "Tests of serial dependence for multivariate time series with arbitrary distributions," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    3. Jean-David Fermanian, 2012. "An overview of the goodness-of-fit test problem for copulas," Papers 1211.4416, arXiv.org.
    4. Dean Fantazzini, 2011. "Analysis of multidimensional probability distributions with copula functions. III," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 24(4), pages 100-130.
    5. Lajmi Lakhal & Louis-Paul Rivest & Belkacem Abdous, 2008. "Estimating Survival and Association in a Semicompeting Risks Model," Biometrics, The International Biometric Society, vol. 64(1), pages 180-188, March.
    6. Kojadinovic, Ivan & Yan, Jun, 2010. "Comparison of three semiparametric methods for estimating dependence parameters in copula models," Insurance: Mathematics and Economics, Elsevier, vol. 47(1), pages 52-63, August.

    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. Zhao, XiaoBing & Zhou, Xian, 2010. "Applying copula models to individual claim loss reserving methods," Insurance: Mathematics and Economics, Elsevier, vol. 46(2), pages 290-299, April.
    2. F. Durante & A. Gatto & F. Ravazzolo, 2024. "Understanding relationships with the Aggregate Zonal Imbalance using copulas," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(2), pages 513-554, April.
    3. Menggang Yu, 2016. "Improving estimation efficiency for semi-competing risks data with partially observed terminal event," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(4), pages 860-874, October.
    4. Huazhen Lin & Ling Zhou & Chunhong Li & Yi Li, 2014. "Semiparametric transformation models for semicompeting survival data," Biometrics, The International Biometric Society, vol. 70(3), pages 599-607, September.
    5. Warne, Anders, 2023. "DSGE model forecasting: rational expectations vs. adaptive learning," Working Paper Series 2768, European Central Bank.
    6. He, W., 2014. "Analysis of multivariate survival data with Clayton regression models under conditional and marginal formulations," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 52-63.
    7. Hengxin Cui & Ken Seng Tan & Fan Yang, 2024. "Portfolio credit risk with Archimedean copulas: asymptotic analysis and efficient simulation," Annals of Operations Research, Springer, vol. 332(1), pages 55-84, January.
    8. Christian Genest & Johanna Nešlehová & Johanna Ziegel, 2011. "Inference in multivariate Archimedean copula models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(2), pages 223-256, August.
    9. Chao Xun & Huan Zheng & Zhaoyu Han, 2024. "Decomposition of air conditioning electricity consumption based on effective duration," PLOS ONE, Public Library of Science, vol. 19(8), pages 1-21, August.
    10. Matthieu Garcin & Dominique Guegan & Bertrand Hassani, 2017. "A novel multivariate risk measure: the Kendall VaR," Documents de travail du Centre d'Economie de la Sorbonne 17008, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    11. Matthieu Garcin & Dominique Guegan & Bertrand Hassani, 2017. "A novel multivariate risk measure: the Kendall VaR," Documents de travail du Centre d'Economie de la Sorbonne 17008r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Apr 2018.
    12. Fei Jiang & Sebastien Haneuse, 2017. "A Semi-parametric Transformation Frailty Model for Semi-competing Risks Survival Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(1), pages 112-129, March.
    13. Gunky Kim & Mervyn J. Silvapulle & Paramsothy Silvapulle, 2007. "Semiparametric estimation of the dependence parameter of the error terms in multivariate regression," Monash Econometrics and Business Statistics Working Papers 1/07, Monash University, Department of Econometrics and Business Statistics.
    14. Zhu Hong & Wang Mei-Cheng, 2015. "A Semi-stationary Copula Model Approach for Bivariate Survival Data with Interval Sampling," The International Journal of Biostatistics, De Gruyter, vol. 11(1), pages 151-173, May.
    15. Menggang Yu & Constantin T. Yiannoutsos, 2015. "Marginal and Conditional Distribution Estimation from Double-sampled Semi-competing Risks Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 87-103, March.
    16. Segers, Johan & Uyttendaele, Nathan, 2013. "Nonparametric estimation of the tree structure of a nested Archimedean copula," LIDAM Discussion Papers ISBA 2013009, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    17. Lin, Feng & Peng, Liang & Xie, Jiehua & Yang, Jingping, 2018. "Stochastic distortion and its transformed copula," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 148-166.
    18. Dongdong Li & X. Joan Hu & Mary L. McBride & John J. Spinelli, 2020. "Multiple event times in the presence of informative censoring: modeling and analysis by copulas," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 573-602, July.
    19. Debashis Ghosh, 2009. "On Assessing Surrogacy in a Single Trial Setting Using a Semicompeting Risks Paradigm," Biometrics, The International Biometric Society, vol. 65(2), pages 521-529, June.
    20. Rodríguez-Lallena, José A. & Úbeda-Flores, Manuel, 2003. "Distribution functions of multivariate copulas," Statistics & Probability Letters, Elsevier, vol. 64(1), pages 41-50, August.

    More about this item

    Keywords

    ;

    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:eee:stapro:v:76:y:2006:i:1:p:10-18. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.