The Annals of Statistics

Linear regression with doubly censored data

Cun-Hui Zhang and Xin Li

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Linear regression with doubly censored responses is considered. Buckley-James-Ritov-type estimators are proposed. Semiparametric information and projective scores are discussed. An expansion of the estimating equations is obtained under fairly general assumptions. Sufficient conditions are given for the asymptotic consistency and normality of the estimators.

Article information

Ann. Statist. Volume 24, Number 6 (1996), 2720-2743.

First available in Project Euclid: 16 September 2002

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Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 62G05: Estimation 62G30: Order statistics; empirical distribution functions
Secondary: 62E20: Asymptotic distribution theory 62G20: Asymptotic properties

Censored data estimating equation $M$-estimator asymptotic linearity consistency normality information operator efficiency survival function weak convergence


Zhang, Cun-Hui; Li, Xin. Linear regression with doubly censored data. Ann. Statist. 24 (1996), no. 6, 2720--2743. doi:10.1214/aos/1032181177.

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