Testing additivity in nonparametric regression under random censorship
Statistics Theory
2008-02-08 v1 Statistics Theory
Abstract
In this paper, we are concerned with nonparametric estimation of the multivariate regression function in the presence of right censored data. More precisely, we propose a statistic that is shown to be asymptotically normally distributed under the additive assumption, and that could be used to test for additivity in the censored regression setting.
Cite
@article{arxiv.0802.1047,
title = {Testing additivity in nonparametric regression under random censorship},
author = {Mohammed Debbarh and Vivian Viallon},
journal= {arXiv preprint arXiv:0802.1047},
year = {2008}
}