Testing additivity in nonparametric regression under random censorship

Mohammed Debbarh and Vivian Viallon

Statistics & Probability Letters, 2008, vol. 78, issue 16, 2584-2591

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 which is shown to be asymptotically normally distributed under the additive assumption, and which could then be used to test for additivity in the multivariate censored regression setting.

Date: 2008
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