A k-Sample Problem with Censored Data

A. Schick and V. Susarla
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A. Schick: State University of New York at Binghamton, Department of Mathematical Sciences
V. Susarla: State University of New York at Binghamton, Department of Mathematical Sciences

A chapter in Mathematical Statistics and Probability Theory, 1987, pp 215-230 from Springer

Abstract: Abstract In this paper, we address the question of asymptotically efficient estimation in randomly right censored regression models. We allow the censoring distributions to depend on the covariate. For simplicity, we consider only situations in which the covariates come from a finite set. We provide a characterization of efficient estimates, describe a general method for the construction of such estimates and carry out this construction when the censoring distributions are known.

Keywords: Censor Data; Local Sequence; Efficient Estimate; Adaptive Estimation; Lebesgue Dominate Convergence Theorem (search for similar items in EconPapers)
Date: 1987
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-94-009-3965-3_20

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DOI: 10.1007/978-94-009-3965-3_20

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