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Published online by Cambridge University Press:  25 February 2013

Efang Kong*
University of Kent at Canterbury
Oliver Linton
University of Cambridge
Yingcun Xia
Nanjing University and National University of Singapore
*Address correspondence to Efang Kong, School of Mathematics, Statistics and Actuarial Science, University of Kent at Canterbury, UK; e-mail:


This paper is concerned with the nonparametric estimation of regression quantiles of a response variable that is randomly censored. Using results on the strong uniform convergence rate of U-processes, we derive a global Bahadur representation for a class of locally weighted polynomial estimators, which is sufficiently accurate for many further theoretical analyses including inference. Implications of our results are demonstrated through the study of the asymptotic properties of the average derivative estimator of the average gradient vector and the estimator of the component functions in censored additive quantile regression models.

Copyright © Cambridge University Press 2013 

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The authors thank Professor Arthur Lewbel (co-editor) and three referees for helpful comments. Xia’s work is partially supported by a grant of NUS R-155-000-121-112.



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