A Sequential Multiple-decision Procedure for Selecting the Best One of Several Normal Populations with a Common Unknown Variance. Ii. Monte Carlo Sampling Results and New Computing Formulae


Book Description

Contents: Statement of the statistical problem S atistical assumptions The experimenter's goal, specification, and requirement Procedure D and the new computing formulae Description of Procedure D Definition of symbols The sampling, stopping, and terminal de cision rules Computation of the stopping statistic Use of Procedure D (method B) with various experimental designs Simplified computing formulae Numerical example Monte Carlo sampling results with Procedure D Description of the sampling procedure Sampling results Discussion of sampling results.




Multiple Decision Procedures


Book Description

Multiple Decision Procedures: Theory and Methodology of Selecting and Ranking Populations provides an encyclopedic coverage of the literature in the area of ranking and selection procedures, summarizing and surveying in a unified manner a majority of more than 600 main references in the bibliography. It also deals with related problems, such as the estimation of unknown ordered parameters. A separate chapter is devoted to information about several tables available in the literature for carrying out various specific procedures. Examples are given in another chapter illustrating applications of these procedures in various practical contexts. Although several books have appeared to date in this area, many of them deal with specific aspects of the field and a limited number of topics. This book contains substantial material not discussed in other books. Audience: this book can serve as a text for a graduate topics course in ranking and selection (as it has done at Purdue University for more than 30 years). It can also serve as a reference for researchers and practitioners in fields such as agriculture, industry, engineering, and behavioral sciences.







AFOSR.


Book Description