Journal of University of Science and Technology of China ›› 2013, Vol. 43 ›› Issue (2): 162-168.DOI: 10.3969/j.issn.0253-2778.2013.02.012

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The empirical Bayes estimation and its superiority for error variance in normal distribution

YANG Fenghao   

  1. Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026, China
  • Received:2012-08-13 Revised:2013-01-04 Online:2013-02-28 Published:2013-02-28

Abstract: Under the conjugate prior distribution of the error variance in normal distribution and the weighted squared error loss function, the Bayes estimator was derived and the parametric empirical Bayes(PEB) estimator was constructed for the error variance. The superiority of the PEB estimation over the uniformly minimum variance unbiased estimation (UMVUE) in terms of the mean-square error (MSE) criterion was studied. In the case where the hyper-parameters of the prior distribution are completely unknown, the superiority of the PEB estimation over the UMVUE under the MSE criterion was investigated with a simulation study.

Key words: error variance, normal distribution, PEB estimation, MSE criterion