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The variation of the posterior variance and Bayesian sample size determination
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Journal Article
The variation of the posterior variance and Bayesian sample size determination
2021
Overview
We consider Bayesian sample size determination using a criterion that utilizes the first two moments of the posterior variance. We study the resulting sample size in dependence on the chosen prior and explore the success rate for bounding the posterior variance below a prescribed limit under the true sampling distribution. Compared with sample size determination based on the average of the posterior variance the proposed criterion leads to an increase in sample size and significantly improved success rates. Generic asymptotic properties are proven, such as an asymptotic expression for the sample size and a sort of phase transition. Our study is illustrated using two real world datasets with Poisson and normally distributed data. Based on our results some recommendations are given.
Publisher
Springer,Springer Berlin Heidelberg,Springer Nature B.V
Subject
/ Chemistry and Earth Sciences
/ Codes
/ Criteria
/ Finance
/ Law
/ Medicine
/ Physics
/ Statistical Theory and Methods
/ Statistics for Business, Management, Economics, Finance, Insurance
/ Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
/ Statistics for Life Sciences
/ Statistics for Life Sciences, Medicine, Health Sciences
/ Statistics for Social Sciences
