Open Access
September, 1990 Time-Sequential Point Estimation Through Estimating Equations
I-Shou Chang, Chao A. Hsiung
Ann. Statist. 18(3): 1378-1388 (September, 1990). DOI: 10.1214/aos/1176347755

Abstract

Time-sequential point estimation is studied in the model of fully parametric censored data and Cox's regression model. Both are investigated in the context of counting processes through estimating equations defined by martingales. The concept of information and a related inequality developed in estimating function theory by Godambe are adapted to these models. These suggest some optimality criteria for choosing stopping times as well as estimators. These lead naturally to some sequential procedures, which are shown to be asymptotically efficient with respect to the above criteria.

Citation

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I-Shou Chang. Chao A. Hsiung. "Time-Sequential Point Estimation Through Estimating Equations." Ann. Statist. 18 (3) 1378 - 1388, September, 1990. https://doi.org/10.1214/aos/1176347755

Information

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

zbMATH: 0734.62084
MathSciNet: MR1062714
Digital Object Identifier: 10.1214/aos/1176347755

Subjects:
Primary: 62L12

Keywords: Asymptotic efficiency , counting processes , Cox's regression , estimating equations , Information , Martingales , stopping times , Time-sequential point estimation

Rights: Copyright © 1990 Institute of Mathematical Statistics

Vol.18 • No. 3 • September, 1990
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