An Optimal Sequential Bernoulli Selection Procedure,

Abstract

This paper describes a new closed adaptive sequential procedure proposed by Bechhofer and Kulkarni for selecting the Bernoulli population which has the largest success probability. The performance of this procedure is compared to that of the Sobel-Huyett single-stage procedure, and to a curtailed version of the single-stage procedure, all of which guarantee the same probability of a correct selection. Optimal properties of the Bechhofer-Kulkarni procedure are stated; quantitative assessments of important performance characteristics of the procedure are given. These demonstrate conclusively the superiority of the new procedure over that of the competing procedures. Relevant areas of application are described. Appropriate literature references are provided. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1984
Accession Number
ADP003841

Entities

People

  • Robert E. Bechhofer

Organizations

  • Cornell University

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  • Data Science
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Fields of Study

  • Mathematics

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  • Regression Analysis.