東京大学政策評価研究教育センター

CREPEDP-21

Number CREPEDP-21
Publication Date April 2018
Title Bayesian Simultaneous Estimation for Means in k Sample Problems
Author(s) Ryo Imai, Tatsuya Kubokawa, Malay Ghosh
Abstract In this paper, we consider the estimation of a mean vector of a multivariate normal population where the mean vector is suspected to be nearly equal to mean vectors of k – 1 other populations. As an alternative to the preliminary test estimator based on the test statistic for testing hypothesis of equal means, we derive empirical and hierarchical Bayes estimators which shrink the sample mean vector toward a pooled mean estimator given under the hypothesis. The minimaxity of those Bayesian estimators are shown, and their performances are investigated by simulation.
Keywords Admissibility, decision theory, empirical Bayes, hierarchical Bayes, k sample problem, minimaxity, pooled estimator, preliminary test estimator, quadratic loss, shrinkage estimator, uniform prior.
Other information Paper in English (18 pages)