BAHADUR REPRESENTATION OF THE KERNEL QUANTILE ESTIMATOR UNDER RANDOM CENSORSHIP

JOURNAL OF MULTIVARIATE ANALYSIS

卷:54

Article

关键词: QUANTILES;    RANDOM CENSORSHIP;    KAPLAN-MEIER ESTIMATOR;    KERNEL ESTIMATOR;    BAHADUR REPRESENTATION;    LAW OF THE ITERATED LOGARITHM;   

DOI  :  10.1006/jmva.1995.1052

来源: Elsevier

【 摘 要 】

In this paper, a representation due to Major and Rejto for the Kaplan-Meier estimator is applied to establish a Bahadur representation for the kernel quantile estimator under random censorship. Comparing it with the product-limit quantile estimator, the convergence rate of the remainder term is substantially improved when F(x) is sufficiently smooth near the true quantile xi(p). As a consequence, a law of the iterated logarithm is also obtained. (C) 1995 Academic Press, Inc.

【 授权许可】

Free