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Estimation and model selection of semiparametric multivariate survival functions under general censorship

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  • Chen, Xiaohong
  • Fan, Yanqin
  • Pouzo, Demian
  • Ying, Zhiliang

Abstract

We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root-n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided.

Suggested Citation

  • Chen, Xiaohong & Fan, Yanqin & Pouzo, Demian & Ying, Zhiliang, 2010. "Estimation and model selection of semiparametric multivariate survival functions under general censorship," Journal of Econometrics, Elsevier, vol. 157(1), pages 129-142, July.
    • Handle: RePEc:eee:econom:v:157:y:2010:i:1:p:129-142
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    2. Barthel, Nicole & Geerdens, Candida & Killiches, Matthias & Janssen, Paul & Czado, Claudia, 2018. "Vine copula based likelihood estimation of dependence patterns in multivariate event time data," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 109-127.
    3. Wu, Weiou & Lau, Marco Chi Keung & Vigne, Samuel A., 2017. "Modelling asymmetric conditional dependence between Shanghai and Hong Kong stock markets," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1137-1149.
    4. Candida Geerdens & Gerda Claeskens & Paul Janssen, 2016. "Copula based flexible modeling of associations between clustered event times," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(3), pages 363-381, July.
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    6. 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.
    7. Cheng, Guang & Zhou, Lan & Chen, Xiaohong & Huang, Jianhua Z., 2014. "Efficient estimation of semiparametric copula models for bivariate survival data," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 330-344.
    8. Juan Lin & Ximing Wu, 2015. "Smooth Tests of Copula Specifications," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 128-143, January.
    9. Gery Geenens & Arthur Charpentier & Davy Paindaveine, 2014. "Probit Transformation for Nonparametric Kernel Estimation of the Copula Density," Working Papers ECARES ECARES 2014-23, ULB -- Universite Libre de Bruxelles.
    10. Tao Sun & Yi Liu & Richard J. Cook & Wei Chen & Ying Ding, 2019. "Copula-based score test for bivariate time-to-event data, with application to a genetic study of AMD progression," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(3), pages 546-568, July.
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    More about this item

    Keywords

    Multivariate survival models Misspecified copulas Penalized pseudo-likelihood ratio Fixed or random censoring Kaplan-Meier estimator;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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