Bouezmarni, Taoufik and Rabhi, Yassir and Fontaine, Charles (2020) 'A semiparametric copula-based estimation of the regression function for right-censored data.' Statistics, 54 (1). pp. 46-58. ISSN 0233-1888
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A semiparametric copula-based estimation of the regression function.pdf - Accepted Version Download (353kB) | Preview |
Abstract
This paper addresses the semiparametric estimation of the regression function in a situation where the response variable is right-censored and the covariate(s) is completely observed. We present a new copula-based method to estimate the regression function. The key concept presented in this manuscript is to write the regression function in terms of the copula density and marginal distributions. We suppose a parametric model for the copula density with unknown parameter(s), and we estimate the marginal distributions of the response and the covariate(s) by the Kaplan–Meier estimator and the empirical distribution, respectively. We establish the asymptotic properties of our estimator and extend it to the multivariate case. The proposed method is then applied to analyse a data-set on lifetime with lung-cancer.
Item Type: | Article |
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Uncontrolled Keywords: | Semiparametric copula-based estimation, regression function, censored data, parametric copula models, Kaplan–Meier estimator |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Mathematical Sciences, Department of |
SWORD Depositor: | Elements |
Depositing User: | Elements |
Date Deposited: | 23 Apr 2020 11:51 |
Last Modified: | 06 Jan 2022 14:12 |
URI: | http://repository.essex.ac.uk/id/eprint/27337 |
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