Testing additivity in nonparametric regression under random censorship

2008/02/07 by Debbarh, Mohammed, Viallon, Vivian
#FOS: Mathematics #Statistics Theory (math.ST)

paper · doi:10.48550/arxiv.0802.1047

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.

Related

• Asymptotic normality for estimators of the additive regression components under random censorship
• Uniform limit laws of the logarithm for nonparametric estimators of the regression function in presence of censored data
• Nonparametric local linear estimation of the relative error regression function for censorship model
• Nonparametric relative error estimation of the regression function for censored data
• Asymptotic properties of the MLE in distributional regression under random censoring