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台湾淡江大学 黄文涛教授:多准则最佳总体选取的经验贝叶斯方法
2015-05-05 00:00   审核人:

报告题目:多准则最佳总体选取的经验贝叶斯方法 (Selecting the Best Population under Multiple Criteria: An Empirical Bayes Approach)主讲人概况:Wen-Tao Huang (黃文涛)博士/教授

报告时间:2015年5月7日(周四)上午9:00

报告地点:南山1号楼415教师休息室

The Speaker:

Prof. Tamkang University,Taiwan

Editor-in-Chief, Inter. J. Inform.and Manag. Sci..

PhD. Department of Statistics,PurdueUniversity,West Lafayette,Indiana,USA, 1972

Institute of Statistical Sciences, Academia Sinica, Associate Fellow (1972-76), Research Fellow (1976-2000).

President ofTaiwanIntellectual Technology and Applied Statistics Association (June / 2006 -June /2008).

Associate Editor: Statistica Sinica (1991-93), J. App Math and Decision Sci ( 1997-2001)

Main Works

Papers published:

J. Applied Math. and Comput.,

Communi. Statistics: Theory and Methods,

Statistics and Probability Letters,

Comput. Statistics & Data Analysis,et al.

There are more than 46 papers published including 25 SCI.

ABSTRACT

Consider k populations whose meanθ(i) and varianceσ(i) are all unknown. For given control valuesθ(0),σ(0) andδ(0), we are interested in selecting some population whose mean is the most close toθ(0) in the qualified subset in which each mean is no further thanδ(0) fromθ(0) and whose variance is less than or equal toσ(0). We focus on the normal populations though its method can be applied to other distributions. A Bayes approach is set up and an empirical Bayes procedure is proposed which has been shown to be asymptotically optimal. Some simulation study is also given.

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