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1999•Communication in Statistics- Theory and MethodsRequires access

Asymptotic improvement of the graybill-deal estimator

Kiyoshi Inoue

Open publisher page 1 citations

Abstract

Two-stage estimators of the common mean of k normal populations are considered, and compared with the Graybill-Deal estimator in terms of asymptotic variance. Some of them are found to be superior to the estimator under regularity conditions. A comparison of the Graybill-Deal estimator, an alternative estimator and the maximum likelihood estimator is made when samples are of the same size. In addition, several simulation results concerning finite sample behaviour of proposed two-stage estimators are presented.

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What this paper is about

Two-stage estimators of the common mean of k normal populations are considered, and compared with the Graybill-Deal estimator in terms of asymptotic variance. Some of them are found to be superior to the estimator under regularity conditions. A comparison of the Graybill-Deal estimator, an alternative estimator and the maximum likelihood estimator is made when samples are of the same size. In addition, several simulation results concerning finite sample behaviour of proposed two-stage estimators are presented.

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Available abstract

Two-stage estimators of the common mean of k normal populations are considered, and compared with the Graybill-Deal estimator in terms of asymptotic variance. Some of them are found to be superior to the estimator under regularity conditions. A comparison of the Graybill-Deal estimator, an alternative estimator and the maximum likelihood estimator is made when samples are of the same size. In addition, several simulation results concerning finite sample behaviour of proposed two-stage estimators are presented.

Key concepts: Estimator, Minimum-variance unbiased estimator, Mathematics, Bias of an estimator, Invariant estimator, Trimmed estimator, Consistent estimator, Efficient estimator

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