EMPIRICAL BAYES AND COMPOUND ESTIMATION OF NORMAL MEANS
Cun‐Hui Zhang · 1997
Abstract: This article concerns the canonical empirical Bayes problem of estimating normal means under squared-error loss. General empirical estimators are derived which are asymptotically minimax and optimal. Uniform convergence and the speed of convergence are considered. The general empirical Bayes estimators are compared with the shrinkage estimators of Stein (1956) and James and Stein (1961). Estimation of the mixture density and its derivatives are also discussed.