Designing experiments for selecting the largest normal mean when the variances are known and unequal: Optimal sample size allocation

DOI10.1016/0378-3758(91)90067-OzbMath0778.62020OpenAlexW1970103537MaRDI QIDQ1176753

Anthony J. Hayter, Robert E. Bechhofer, Ajit C. Tamhane

Publication date: 25 June 1992

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(91)90067-o

zbMATH Keywords

normal populationsoptimal allocationlargest meanprobability of correct selectionunknown meanssample meanspreference zoneindifference-zone approachknown variancesnatural single-stage selection procedure

Mathematics Subject Classification ID

Statistical ranking and selection procedures (62F07)

Related Items (4)

Bayesian look ahead one stage sampling allocations for selecting the largest normal mean ⋮ Selection of the Best Normal Population: A New Exact Solution, Asymptotically Optimal Whenk=2 ⋮ Bayesian look ahead one-stage sampling allocations for selection of the best population ⋮ Selecting the Best Exponential Population When the Scale Parameters are Bounded

Cites Work

• The Most-Economical Character of Some Bechhofer and Sobel Decision Rules
• A Bayesian Approach to Ranking and Selection of Related Means With Alternatives to Analysis-of-Variance Methodology
• A Single-Sample Multiple Decision Procedure for Ranking Means of Normal Populations with known Variances
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