Asymptotic normality for estimators of the additive regression components under random censorship

2006/12/18 by Mohammed Debbarh, Vivian Viallon, Debbarh, M. +1
Mathematics · Computer Science · Decision Sciences · #Statistical Methods and Inference #Bayesian Methods and Mixture Models #Probability and Risk Models

paper · pdf · doi:10.48550/arxiv.math/0612507

Abstract

We establish asymptotic normality for estimators of the additive regression components under random censorship. To build our estimators, we couple the marginal integration method (Newey (1994)) with an initial Inverse Probability of Censoring Weighted estimator of the multivariate censored regression function introduced by Carbonez et al. (1995) and Kohler et al. (2002). Asymptotic confidence bands are derived from our result.

Citations

• Remarks on Some Nonparametric Estimates of a Density Function

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