A Berry–Esseen type bound in kernel density estimation for strong mixing censored samples

In this paper, we discuss the estimation of a density function based on censored data by the kernel smoothing method when the survival and the censoring times form a stationary α -mixing sequence. A Berry–Esseen type bound is derived for the kernel density estimator at a fixed point x . For practical purposes, a randomly weighted estimator of the density function is also constructed and investigated.