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Shrinkage Estimation of Regression Coefficients From Censored Data With Multiple Observations

  • S. E. Ahmed
Part of the Lecture Notes in Statistics book series (LNS, volume 148)

Abstract

This paper considers the preliminary test and Stein-type estimation of regression parameters in exponential regression failure time distribution. We consider a situation where the lifetime data may be right censored with multiple observations taken at each regression vector. We propose improved estimators of the regression vector when it is suspected that the true regression parameter vectors may be restricted to a linear subspace. The large sample risk properties of the proposed estimators are derived. The relative merits of the proposed estimators are discussed.

Keywords

Maximum Likelihood Estimator Local Alternative Shrinkage Estimator Observe Information Matrix Shrinkage Estimation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer Science+Business Media New York 2001

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  • S. E. Ahmed

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