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Mean square error matrix superiority of Empirical Bayes Estimators under misspecification

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A Correction to this article was published on 01 June 1996

Summary

In this paper we investigate Empirical Bayes Estimators (EBE) in a misspecified linear regression model. Comparisons are made between the EBE and the Ordinary Least Squares Estimator (OLSE) in terms of the Matrix Mean Square Error Criterion (MMSE). Conditions are derived under which the EBE is better than OLSE. Finally we examine the superiority of the EBE-based predictor over the OLSE-predictor.

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Authors and Affiliations

  1. Department of Mathematics, University of Science and Technology of China, Hefei, China

    L. Wei

  2. Department of Statistics, University of Dortmund, 44221, Dortmund, Germany

    G. Trenkler

Authors
  1. L. Wei
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  2. G. Trenkler
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Additional information

An erratum to this article is available at http://dx.doi.org/10.1007/BF02562691.

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Wei, L., Trenkler, G. Mean square error matrix superiority of Empirical Bayes Estimators under misspecification. Test 4, 187–205 (1995). https://doi.org/10.1007/BF02563109

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  • DOI: https://doi.org/10.1007/BF02563109

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