J4 ›› 2011, Vol. 46 ›› Issue (11): 89-95.

• Articles • Previous Articles     Next Articles

The superiority of the Bayes linear unbiased minimum Variance estimator under balanced loss function

LIU Xie-jin1, MIAO Bai-qi2   

  1. 1. Department of Mathematics and Computional Science, Huainan Normal University, Huainan 232038, Anhui, China;
     2. Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026, Anhui, China
  • Received:2010-12-10 Online:2011-11-20 Published:2011-11-30


The superiority of the Bayes linear unbiased minimum variance (BLUMV) estimator with respect to the optimally weighted least square (OWLS) estimator of unknown parameter was studied in terms of the balanced loss risk function criterion, and the two estimators can converge to the same one under a certain condition. The superiority of the BLUMV estimator over the OWLS estimator was studied under predictive Pitman closeness (PRPC) criterion.

Key words: Bayes linear unbiased minimum variance estimator; least square estimator; optimally weighted least square estimator; balanced loss risk function criterion; predictive Pitman closeness criterion

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