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December, 1985 A Large Sample Study of Generalized Maximum Likelihood Estimators from Incomplete Data Via Self-Consistency
Wei-Yann Tsai, John Crowley
Ann. Statist. 13(4): 1317-1334 (December, 1985). DOI: 10.1214/aos/1176349740

Abstract

Self-consistent estimators for estimating distribution functions from incomplete data are presented. In many cases these estimators are also generalized maximum likelihood estimators. In this paper we discuss the theoretical properties of such estimators: existence, uniform consistency, law of the iterated logarithm, and weak convergence. Applications to the product limit estimator for right-censored data and to the estimator proposed by Turnbull (1974, 1976) for doubly (right- and left-) censored data are also given.

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Wei-Yann Tsai. John Crowley. "A Large Sample Study of Generalized Maximum Likelihood Estimators from Incomplete Data Via Self-Consistency." Ann. Statist. 13 (4) 1317 - 1334, December, 1985. https://doi.org/10.1214/aos/1176349740

Information

Published: December, 1985
First available in Project Euclid: 12 April 2007

zbMATH: 0611.62038
MathSciNet: MR811495
Digital Object Identifier: 10.1214/aos/1176349740

Subjects:
Primary: 62E20
Secondary: 62G05

Rights: Copyright © 1985 Institute of Mathematical Statistics

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Vol.13 • No. 4 • December, 1985
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