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- W2067351981 abstract "For the mean vector of a p-variate normal distribution (<TEX>$p{geq}3$</TEX>), the optimal estimation within the class of James-Stein type decision rules under the quadratic loss are given when the underlying distribution is that of a variance mixture of normals and when the norm <TEX>${parallel}underline{{theta}}{parallel}$</TEX> in known. It also demonstrated that the optimal estimation within the class of Lindley type decision rules under the same loss when the underlying distribution is the previous type and the norm <TEX>${parallel}{theta}-overline{theta}underline{1}{parallel}$</TEX> with <TEX>$overline{theta}=frac{1}{p}sumlimits_{i=1}^{n}{theta}_i$</TEX> and <TEX>$underline{1}=(1,{cdots},1)^{prime}$</TEX> is known." @default.
- W2067351981 created "2016-06-24" @default.
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- W2067351981 date "2012-09-30" @default.
- W2067351981 modified "2023-09-23" @default.
- W2067351981 title "Optimal Estimation within Class of James-Stein Type Decision Rules on the Known Norm" @default.
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- W2067351981 doi "https://doi.org/10.13160/ricns.2012.5.3.186" @default.
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