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Empirical Bayes Estimation with Random Censoring

  • TaChen Liang
Article

Abstract

We study empirical Bayes estimation for exponential distributions based on randomly censored data. An empirical Bayes estimator φ̃n is constructed. The rate of asymptotic optimality of φ̃n is investigated. It is shown that under certain conditions, the regret of φ̃n converges to zero at a rate O(ln4n/n1/2), where n is the number of past data available when the present estimation problem is considered.

AMS Subject Classification

62C12 

Keywords

Kaplan-Meier estimator Random censoring Rate of convergence Regret 

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Copyright information

© Grace Scientific Publishing 2010

Authors and Affiliations

  1. 1.Department of MathematicsWayne State UniversityDetroitUSA

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