Nonparametric estimation of mean residual quantile function under right censoring

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.

KEYWORDS:

• Non-parametric estimator
• mean residual quantile function
• kernel smoothing

Acknowledgements

We thank the editor and the anonymous reviewer for their constructive comments, which helped us to improve the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCiD

N.N. Midhu http://orcid.org/0000-0001-7570-3446