论文标题
James-Stein估计器的合奏最小值
Ensemble minimaxity of James-Stein estimators
论文作者
论文摘要
本文讨论了基于异质观测的多元正常平均值的估计。在异性范围内，估计量在具有较大差异的坐标上缩小了更多的估计值，这似乎是可取的。尽管它们不一定是普通意义上的最小值，但我们表明，这种詹姆斯 - 斯坦型估计量可以是合奏的minimax，而对整体风险的最小值，这与Efron和Morris的经验贝叶斯观点有关。
This article discusses estimation of a multivariate normal mean based on heteroscedastic observations. Under heteroscedasticity, estimators shrinking more on the coordinates with larger variances, seem desirable. Although they are not necessarily minimax in the ordinary sense, we show that such James-Stein type estimators can be ensemble minimax, minimax with respect to the ensemble risk, related to empirical Bayes perspective of Efron and Morris.
