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December, 1984 Bayesianly Justifiable and Relevant Frequency Calculations for the Applied Statistician
Donald B. Rubin
Ann. Statist. 12(4): 1151-1172 (December, 1984). DOI: 10.1214/aos/1176346785


A common reaction among applied statisticians is that the Bayesian statistician's energies in an applied problem must be directed at the a priori elicitation of one model specification from which an optimal design and all inferences follow automatically by applying Bayes's theorem to calculate conditional distributions of unknowns given knowns. I feel, however, that the applied Bayesian statistician's tool-kit should be more extensive and include tools that may be usefully labeled frequency calculations. Three types of Bayesianly justifiable and relevant frequency calculations are presented using examples to convey their use for the applied statistician.


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Donald B. Rubin. "Bayesianly Justifiable and Relevant Frequency Calculations for the Applied Statistician." Ann. Statist. 12 (4) 1151 - 1172, December, 1984.


Published: December, 1984
First available in Project Euclid: 12 April 2007

zbMATH: 0555.62010
MathSciNet: MR760681
Digital Object Identifier: 10.1214/aos/1176346785

Primary: 62A15
Secondary: 62F15 , 62L10 , 62P99

Keywords: 62-07 , Calibration , Empirical Bayes , inference , model monitoring , operating characteristics , posterior predictive checks , Stopping rules

Rights: Copyright © 1984 Institute of Mathematical Statistics

Vol.12 • No. 4 • December, 1984
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