Selecting the best binomial population: Parametric empirical Bayes approach

DOI10.1016/0378-3758(89)90036-0zbMath0685.62029OpenAlexW2031704270MaRDI QIDQ1262041

Ta Chen Liang, Shanti S. Gupta

Publication date: 1989

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(89)90036-0

zbMATH Keywords

selectionloss functionrates of convergencebinomial distributionBayes riskminimum Bayes riskbest populationconjugate beta priorempirical Bayes selection ruleunknown hyperparameters

Mathematics Subject Classification ID

Statistical ranking and selection procedures (62F07) Empirical decision procedures; empirical Bayes procedures (62C12)

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Empirical bayes estimation of binomial parameter with symmetric priors, Empirical Bayes rules for selecting the most and least probable multivariate hypergeometric event, Minimax type procedures for nonparametric selection of the “best” population with partially classified data, Rank verification for exponential families, On empirical bayes rules for selecting the best hypergeometric population, A program for sequential allocation of three Bernoulli populations, A Bayesian Inference and Stochastic Dynamic Programming Approach to Determine the Best Binomial Distribution, Selection of the best Bernoulli population provided it is better than a control: an empirical Bayes approach, Bayesian approach to two-stage phase trial

Cites Work

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• Some thoughts on empirical Bayes estimation
• Optimal properties of the Bechhofer-Kulkarni Bernoulli selection procedure
• On selecting the largest success probability under unequal sample sizes
• Probability Inequalities for Sums of Bounded Random Variables
• The Empirical Bayes Approach to Statistical Decision Problems