Journal of the
Korean Mathematical Society JKMS

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.

Keywords: censored sample, non-parametric regression model, weighted kernel estimator, asymptotic normality

MSC numbers: 62G05