随机效应模型中方差分量的Bayes估计及其优良性
The Superiorities of Bayes Estimation for Variance Components in Random Effects Model
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摘要: 在平衡单向分类随机效应模型中, 假定方差分量具有共轭先验分布, 在加权平方损失下导出了方差分量的Bayes估计; 在均方误差准则下研究了方差分量的Bayes估计相对于经典统计方法中的ANOVA估计的优良性. 最后, 给出了本文主要结果的一个注释.Abstract: The Bayes estimators of variance components are derived under weighted square loss function for the balanced one-way classification random effects model with the assumption that variance component has the conjugate prior distribution. The superiorities of the Bayes estimators for variance components to traditional ANOVA estimators are studied in terms of the mean square error (MSE) criterion. Finally, a remark for main results is given.