Asymptotic normality for estimators of the additive regression components under random censorship
Statistics Theory
2008-03-07 v2 Statistics Theory
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.
Keywords
Cite
@article{arxiv.math/0612507,
title = {Asymptotic normality for estimators of the additive regression components under random censorship},
author = {M. Debbarh and V. Viallon},
journal= {arXiv preprint arXiv:math/0612507},
year = {2008}
}
Comments
21 pages, 1 figures