Minimaxity of empirical bayes estimators of the means of independent normal variables with unequal variances
Minimaxity of empirical bayes estimators of the means of independent normal variables with unequal variances
复制标题
具有不等方差的独立正态变量均值的经验贝叶斯估计量的极小极大
DOI：
10.1080/03610929308831140
复制
发表时间：
1993
影响因子：
0.8
通讯作者：
Yuan
中科院分区：
文献类型：
--
作者：
Nobuo Shinozaki;Yuan
当方差不等且损失为误差平方和时，考虑正态均值同时估计的问题。当共同先验分布由平均值为 0 的正态分布给出时，研究经验贝叶斯估计量的极小极大或非极小极大。还给出了当损失是误差平方和的加权时的情况的极小极大结果。给出了蒙特卡罗模拟结果，以将经验贝叶斯估计器的风险行为与其他极小极大估计器的风险行为进行比较。
The problem of simultaneous estimation of normal means is considered when variances are unequal and the loss is sum of squared errors. Minimaxity or non-minimaxity of empirical Bayes estimators is investigated when the common prior distribution is given by normal one with mean 0. Minimaxity results for the case when the loss is a weighted sum of squared errors is also given. Monte Carlo simulation results are given to compare the risk behavior of the empirical Bayes estimator with those of other minimax ones.