Bivariate censored regression relying on a new estimator of the joint distribution function |
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Authors: | Olivier Lopez Philippe Saint-Pierre |
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Institution: | Laboratoire de Statistique Théorique et Appliquée, Université Paris VI, 4 place Jussieu, 75252 Paris Cedex 5, France |
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Abstract: | In this paper we study a class of M -estimators in a regression model under bivariate random censoring and provide a set of sufficient conditions that ensure asymptotic n1/2-convergence. The cornerstone of our approach is a new estimator of the joint distribution function of the censored lifetimes. A copula approach is used to modelize the dependence structure between the bivariate censoring times. The resulting estimators present the advantage of being easily computable. A simulation study enlighten the finite sample behavior of this technique. |
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Keywords: | Bivariate censoring M-estimation Regression modeling Copula functions Kaplan&ndash Meier estimator i i d representations |
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