Optimal Bayes procedures for selecting the better of two Bernoulli populations

DOI10.1016/0378-3758(86)90106-0zbMath0622.62023OpenAlexW1997467935MaRDI QIDQ1091056

Radhika V. Kulkarni, Vidyadhar G. Kulkarni

Publication date: 1987

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(86)90106-0

zbMATH Keywords

minimaxapproximationsclinical trialsstopping rulerecursion equationsBernoulli populationsexpected total number of observationsadaptive sequential selection proceduresEmpirical proceduresindependent Beta prior densitieslarger success probabilityoptimal Bayes proceduresymmetric Beta priorsuniform prior distributions

Mathematics Subject Classification ID

Bayesian problems; characterization of Bayes procedures (62C10) Sequential statistical design (62L05) Sequential statistical analysis (62L10) Statistical ranking and selection procedures (62F07) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items (2)

Optimal Bayes procedures for selecting the better of two Bernoulli populations ⋮ A program for sequential allocation of three Bernoulli populations

Cites Work

• Optimal properties of the Bechhofer-Kulkarni Bernoulli selection procedure
• Optimal Bayes procedures for selecting the better of two Bernoulli populations
• Equal probability of correct selection for bernoulli selection procedures
• A monte carlo study of the performance of a closed adaptive sequential procedure for selecting the best bernoulli population
• On the performance characteristics of a closed adaptive sequential procedure for selecting the best bernoulli population
• on the stochastic minimization of sample size by the bechhofer-kulkarni bernoulli sequential selection procedure
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