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Admissibility of the usual estimators under error-in-variables superpopulation model

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  • Zou, Guohua
  • Liang, Hua

Abstract

In this paper, we first point out that a result in Mukhopadhyay (1994) on the optimality of the usual estimator sy2 of finite population variance is not true. We then give a necessary and sufficient condition for ((1 - f)/n) sy2 (where f means the sampling fraction) as the estimator of the precision of the sample mean s to be admissible in the class of quadratic estimators. Our result shows that there is virtual difference between the admissibility of estimators under error-in-variables superpopulation model and the usual superpopulation model. We also show that the improved estimator ((1 - f)/n) ((n - 1)/(n + 1)) sy2 over ((1 - f)/n) sy2 under the usual superpopulation model without measurement errors is admissible in the class of quadratic estimators.

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Bibliographic Info

Article provided by Elsevier in its journal Statistics & Probability Letters.

Volume (Year): 32 (1997)
Issue (Month): 3 (March)
Pages: 301-309

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Handle: RePEc:eee:stapro:v:32:y:1997:i:3:p:301-309

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Related research

Keywords: Superpopulation model Measurement error Quadratic estimator Admissibility;

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