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April 1996 Nonparametric likelihood ratio confidence bands for quantile functions from incomplete survival data
Gang Li, Myles Hollander, Ian W. McKeague, Jie Yang
Ann. Statist. 24(2): 628-640 (April 1996). DOI: 10.1214/aos/1032894455

Abstract

The purpose of this paper is to derive confidence bands for quantile functions using a nonparametric likelihood ratio approach. The method is easy to implement and has several appealing properties. It applies to right-censored and left-truncated data, and it does not involve density estimation or even require the existence of a density. Previous approaches (e.g., bootstrap) have imposed smoothness conditions on the density. The performance of the proposed method is investigated in a Monte Carlo study, and an application to real data is given.

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Gang Li. Myles Hollander. Ian W. McKeague. Jie Yang. "Nonparametric likelihood ratio confidence bands for quantile functions from incomplete survival data." Ann. Statist. 24 (2) 628 - 640, April 1996. https://doi.org/10.1214/aos/1032894455

Information

Published: April 1996
First available in Project Euclid: 24 September 2002

zbMATH: 0859.62047
MathSciNet: MR1394978
Digital Object Identifier: 10.1214/aos/1032894455

Subjects:
Primary: 62G07
Secondary: 62G20

Rights: Copyright © 1996 Institute of Mathematical Statistics

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Vol.24 • No. 2 • April 1996
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