The Annals of Statistics

Linear regression with doubly censored data

Cun-Hui Zhang and Xin Li

Full-text: Open access

Abstract

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

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

Dates
First available in Project Euclid: 16 September 2002

Permanent link to this document
http://projecteuclid.org/euclid.aos/1032181177

Digital Object Identifier
doi:10.1214/aos/1032181177

Mathematical Reviews number (MathSciNet)
MR1425976

Zentralblatt MATH identifier
0898.62042

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

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

Citation

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


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