• Niu, Si-Li ;
  • Li, Qlan-Ru
  • Published : 2007.05.31


Consider the regression model $Y_i=g(x_i)+e_i\;for\;i=1,\;2,\;{\ldots},\;n$, where: (1) $x_i$ are fixed design points, (2) $e_i$ are independent random errors with mean zero, (3) g($\cdot$) is unknown regression function defined on [0, 1]. Under $Y_i$ are censored randomly, we discuss the asymptotic normality of the weighted kernel estimators of g when the censored distribution function is known or unknown.


censored sample;non-parametric regression model;weighted kernel estimator;asymptotic normality


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