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.
Publié le : 1985-12-14
Classification:
Generalized maximum likelihood estimator,
self-consistency,
incomplete data,
implicit function theorem,
uniform consistency,
law of the iterated logarithm,
weak convergence,
product limit estimator,
censored data,
62E20,
62G05
@article{1176349740,
author = {Tsai, Wei-Yann and Crowley, John},
title = {A Large Sample Study of Generalized Maximum Likelihood Estimators from Incomplete Data Via Self-Consistency},
journal = {Ann. Statist.},
volume = {13},
number = {1},
year = {1985},
pages = { 1317-1334},
language = {en},
url = {http://dml.mathdoc.fr/item/1176349740}
}
Tsai, Wei-Yann; Crowley, John. A Large Sample Study of Generalized Maximum Likelihood Estimators from Incomplete Data Via Self-Consistency. Ann. Statist., Tome 13 (1985) no. 1, pp. 1317-1334. http://gdmltest.u-ga.fr/item/1176349740/