Modified Kernel Quantile Estimator Under Censoring

摘要

Based on right-censored data from a lifetime distribution F sub o, a modification of the kernal quantile estimator is proposed. The advantage of this estimator is that the data play a role in the degree of smoothing of the estimator while retaining the desirable features of the kernel estimator. Convergence in probability and almost sure convergence of the estimator are discussed. Also, asymptotic normality and confidence bands are presented and some examples are given. Keywords: Nonparametric quantile estimation. (KR)