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October 2014 Maximum smoothed likelihood estimators for the interval censoring model
Piet Groeneboom
Ann. Statist. 42(5): 2092-2137 (October 2014). DOI: 10.1214/14-AOS1256

Abstract

We study the maximum smoothed likelihood estimator (MSLE) for interval censoring, case 2, in the so-called separated case. Characterizations in terms of convex duality conditions are given and strong consistency is proved. Moreover, we show that, under smoothness conditions on the underlying distributions and using the usual bandwidth choice in density estimation, the local convergence rate is $n^{-2/5}$ and the limit distribution is normal, in contrast with the rate $n^{-1/3}$ of the ordinary maximum likelihood estimator.

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Piet Groeneboom. "Maximum smoothed likelihood estimators for the interval censoring model." Ann. Statist. 42 (5) 2092 - 2137, October 2014. https://doi.org/10.1214/14-AOS1256

Information

Published: October 2014
First available in Project Euclid: 11 September 2014

zbMATH: 1305.62142
MathSciNet: MR3262478
Digital Object Identifier: 10.1214/14-AOS1256

Subjects:
Primary: 62G05 , 62N01
Secondary: 62G20

Keywords: asymptotic distribution , consistency , integral equations , interval censoring , kernel estimators , maximum smoothed likelihood estimator , smoothed maximum likelihood estimator

Rights: Copyright © 2014 Institute of Mathematical Statistics

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Vol.42 • No. 5 • October 2014
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