Author:
Kong Efang,Linton Oliver,Xia Yingcun
Abstract
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.
Publisher
Cambridge University Press (CUP)
Subject
Economics and Econometrics,Social Sciences (miscellaneous)
Reference63 articles.
1. A Bernstein-type inequality for U-statistics and U-processes;Arcones;Statistics and Probability Letters,1995
2. Nonparametric estimation of an additive quantile regression model;Horowitz;Journal of the American Statistical Association,2005
3. Nonlinear regression with censored data;Heuchenne;Technometrics,2007
4. Nonparametric censored and truncated regression;Lewbel;Econometrica,2002
5. Investigating smooth multiple regression by the method of average derivatives;Härdle;Journal of American Statistical Association,1989
Cited by
10 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献