科研之友
微信
新浪微博
Facebook
分享链接
摘要
The seminal work of Stein (1956) showed that the maximum likelihood estimator (MLE) of the mean vector of a p-dimensional multivariate normal distribution is inadmissible under the squared error loss function when p >= 3 and proposed the Stein estimator that dominates the MLE. Later, James and Stein (1961) proposed the James-Stein estimator for the same problem and received much more attention than the original Stein estimator. We re-examined the Stein estimator and conducted an analytic comparison with the James-Stein estimator. We found that the Stein estimator outperforms the James-Stein estimator under certain scenarios and derived the sufficient conditions.
