Linear regression with doubly censored data

Cun-Hui Zhang; Xin Li

doi:10.1214/aos/1032181177

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Linear regression with doubly censored data

Cun-Hui Zhang Xin Li

Year: 1996 Journal: The Annals of Statistics Vol: 24 (6) Publisher: Institute of Mathematical Statistics

DOI: 10.1214/aos/1032181177

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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.

Keywords:

Mathematics Estimator Asymptotic distribution Consistency (knowledge bases) Linear regression Strong consistency Statistics Censored regression model Linear model Semiparametric regression Regression analysis Estimating equations Regression Applied mathematics Econometrics Discrete mathematics

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Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Bayesian Methods and Mixture Models

Physical Sciences → Computer Science → Artificial Intelligence

Statistical Distribution Estimation and Applications

Physical Sciences → Mathematics → Statistics and Probability

Linear regression with doubly censored data

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