不同损失函数下Poisson分布参数的E-Bayes估计及其E-MSE
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韩明
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E-Bayesian Estimation and Its E-MSE of Poisson Distribution Parameter Under Different Loss Functions
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Ming Han
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表 4 $\widehat \lambda_{EBi}$和E-MSE$(\widehat{\lambda}_{EBi})\ (i=1, 2, 3)$的计算结果($\lambda=4$)
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| $n$ | 20 | 40 | 60 | 80 | 100 | | $\widehat\lambda_{EB1}$ | 3.9248 | 3.9617 | 3.9720 | 3.9787 | 3.9885 | | $\widehat\lambda_{EB2}$ | 3.9003 | 3.9493 | 3.9638 | 3.9725 | 3.9886 | | $\widehat\lambda_{EB3}$ | 3.8760 | 3.9370 | 3.9555 | 3.9663 | 3.9887 | | E-MSE$(\widehat\lambda_{EB1})$ | 0.1915 | 0.0978 | 0.0656 | 0.0494 | 0.0395 | | E-MSE$(\widehat\lambda_{EB2})$ | 0.1921 | 0.0980 | 0.0657 | 0.0495 | 0.0397 | | E-MSE$(\widehat\lambda_{EB3})$ | 0.1939 | 0.0984 | 0.0659 | 0.0496 | 0.0398 |
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