Nonparametric estimation of mean residual quantile function under right censoring

Article Type

Research Article

Publication Title

Journal of Applied Statistics

Abstract

In this paper, we develop non-parametric estimation of the mean residual quantile function based on right-censored data. Two non-parametric estimators, one based on the empirical quantile function and the other using the kernel smoothing method, are proposed. Asymptotic properties of the estimators are discussed. Monte Carlo simulation studies are conducted to compare the two estimators. The method is illustrated with the aid of two real data sets.

First Page

1856

Last Page

1874

DOI

10.1080/02664763.2016.1238046

Publication Date

7-27-2017

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