Bayesian look ahead one-stage sampling allocations for selection of the best population

DOI10.1016/0378-3758(95)00169-7zbMath0854.62018OpenAlexW2089425220MaRDI QIDQ1923396

Shanti S. Gupta, Klaus J. Miescke

Publication date: 7 October 1996

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(95)00169-7

zbMATH Keywords

largest meanunknown meanslinear losscommon known varianceindependent normal populationsindependent conjugate priorsBayesian look aheadBayesian selection proceduresoptimum sampling allocations

Mathematics Subject Classification ID

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

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Cites Work

• On combining selection and estimation in the search for the largest binomial parameter
• Sequential selection procedures. A decision theoretic approach
• 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
• Functions decreasing in transposition and their applications in ranking problems
• Bayesian look ahead one stage sampling allocations for selecting the largest normal mean
• Dynamic Allocation in Survey Sampling
• A Bayesian Approach to Ranking and Selection of Related Means With Alternatives to Analysis-of-Variance Methodology
• Bayesian subset selection for additive and linear loss function
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