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Smoothed Estimator of Quantile Residual Lifetime for Right Censored Data

ZHANG, Li, LIU, Peng, ZHOU, Yong (2015) Smoothed Estimator of Quantile Residual Lifetime for Right Censored Data. Journal of Systems Science and Complexity, . ISSN 1559-7067. (doi:10.1007/s11424-015-3067-7) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

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It is of great interest to estimate quantile residual lifetime in medical science and many other fields. In survival analysis, Kaplan-Meier (K-M) estimator has been widely used to estimate the survival distribution. However, it is well-known that the K-M estimator is not continuous, thus it can not always be used to calculate quantile residual lifetime. In this paper, the authors propose a kernel smoothing method to give an estimator of quantile residual lifetime. By using modern empirical process techniques, the consistency and the asymptotic normality of the proposed estimator are provided neatly. The authors also present the empirical small sample performances of the estimator. Deficiency is introduced to compare the performance of the proposed estimator with the naive unsmoothed estimator of the quantile residaul lifetime. Further simulation studies indicate that the proposed estimator performs very well.

Item Type: Article
DOI/Identification number: 10.1007/s11424-015-3067-7
Uncontrolled keywords: Empirical process, estimating equation, influence curve, Kaplan-Meier estimator, kernel smoothing, quantile residual lifetime, right censored data.
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Peng Liu
Date Deposited: 09 Aug 2019 16:45 UTC
Last Modified: 12 Aug 2019 10:42 UTC
Resource URI: (The current URI for this page, for reference purposes)
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