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June, 1986 Some Asymptotic Properties of Kernel Estimators of a Density Function in Case of Censored Data
Jan Mielniczuk
Ann. Statist. 14(2): 766-773 (June, 1986). DOI: 10.1214/aos/1176349954

Abstract

The kernel estimator is a widely used tool for the estimation of a density function. In this paper its adaptation to censored data using the Kaplan-Meier estimator is considered. Asymptotic properties of four estimators, arising naturally as a result of considering various types of bandwidths, are investigated. In particular we show that (i) both proposed estimators stemming from the nearest neighbor estimator have censoring-free variances and (ii) one of them is pointwise mean consistent.

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Jan Mielniczuk. "Some Asymptotic Properties of Kernel Estimators of a Density Function in Case of Censored Data." Ann. Statist. 14 (2) 766 - 773, June, 1986. https://doi.org/10.1214/aos/1176349954

Information

Published: June, 1986
First available in Project Euclid: 12 April 2007

zbMATH: 0603.62047
MathSciNet: MR840530
Digital Object Identifier: 10.1214/aos/1176349954

Subjects:
Primary: 62G05
Secondary: 60F15

Rights: Copyright © 1986 Institute of Mathematical Statistics

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Vol.14 • No. 2 • June, 1986
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