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March, 1990 Estimation in a Linear Regression Model with Censored Data
Y. Ritov
Ann. Statist. 18(1): 303-328 (March, 1990). DOI: 10.1214/aos/1176347502


We consider the semiparametric linear regression model with censored data and with unknown error distribution. We describe estimation equations of the Buckley-James type that admit $\sqrt n$-consistent and asymptotically normal solutions. The derived estimator is efficient at a particular error distribution. We show the equivalence between this type of estimator and an estimator based on a linear rank test suggested by Tsiatis. This equivalence is an extension of a basic equivalence between Doob type martingales and counting process martingales shown by Ritov and Wellner. An extension to an estimator that is efficient everywhere is discussed.


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Y. Ritov. "Estimation in a Linear Regression Model with Censored Data." Ann. Statist. 18 (1) 303 - 328, March, 1990.


Published: March, 1990
First available in Project Euclid: 12 April 2007

zbMATH: 0713.62045
MathSciNet: MR1041395
Digital Object Identifier: 10.1214/aos/1176347502

Primary: 62G20
Secondary: 62G05

Keywords: Buckley-James estimator , counting process , Kaplan-Meier estimator , Martingales

Rights: Copyright © 1990 Institute of Mathematical Statistics


Vol.18 • No. 1 • March, 1990
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