Bayesian look ahead one stage sampling allocations for selecting the largest normal mean

DOI10.1007/BF02926410zbMath0807.62026OpenAlexW2067143954MaRDI QIDQ1342798

Shanti S. Gupta, Klaus J. Miescke

Publication date: 1 March 1995

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02926410

zbMATH Keywords

0-1 lossunknown meanslinear losscommon known varianceBayes selection ruleindependent normal populationsoptimum allocations of additional observationssamples of unequal sizes

Mathematics Subject Classification ID

Bayesian inference (62F15) Statistical ranking and selection procedures (62F07)

Related Items (6)

Single-sample Bayes and empirical Bayes rules for ranking and estimating multinomial probabilities ⋮ Top-\(\kappa\) selection with pairwise comparisons ⋮ Bayesian look ahead one-stage sampling allocations for selection of the best population ⋮ An essentially complete class of multiple decision procedures ⋮ Sequentual first-crossing look-ahead procedure for selecting a population with the largest mean in normal-normal model ⋮ Sequential selection procedures: using sample means to improve efficiency

Cites Work

• Statistical decision theory and Bayesian analysis. 2nd ed
• On selecting the largest success probability under unequal sample sizes
• Designing experiments for selecting the largest normal mean when the variances are known and unequal: Optimal sample size allocation
• A Bayesian Approach to Ranking and Selection of Related Means With Alternatives to Analysis-of-Variance Methodology
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