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September, 1986 Local Convergence of Empirical Measures in the Random Censorship Situation with Application to Density and Rate Estimators
Helmut Schafer
Ann. Statist. 14(3): 1240-1245 (September, 1986). DOI: 10.1214/aos/1176350063

Abstract

In this paper, we study the local deviations of the empirical measure defined by the Kaplan-Meier (1958) estimator for the survival function. The results are applied to derive best rates of convergence for kernel estimators for the density and hazard rate function in the random censorship model.

Citation

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Helmut Schafer. "Local Convergence of Empirical Measures in the Random Censorship Situation with Application to Density and Rate Estimators." Ann. Statist. 14 (3) 1240 - 1245, September, 1986. https://doi.org/10.1214/aos/1176350063

Information

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

zbMATH: 0612.62058
MathSciNet: MR856819
Digital Object Identifier: 10.1214/aos/1176350063

Subjects:
Primary: 62G05
Secondary: 62P10

Keywords: Convergence rates , empirical measures , kernel density estimation , random censorship model , sample-point-dependent bandwidths

Rights: Copyright © 1986 Institute of Mathematical Statistics

Vol.14 • No. 3 • September, 1986
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