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arXiv · 2110.15625

Neyman-Pearson lemma for Bayes factors

Andrew Fowlie
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Abstract

We point out that the Neyman-Pearson lemma applies to Bayes factors if we consider expected type-1 and type-2 error rates. That is, the Bayes factor is the test statistic that maximises the expected power for a fixed expected type-1 error rate. For Bayes factors involving a simple null hypothesis, the expected type-1 error rate is just the completely frequentist type-1 error rate. Lastly we remark on connections between the Karlin-Rubin theorem and uniformly most powerful tests, and Bayes factors. This provides frequentist motivations for computing the Bayes factor and could help reconcile Bayesians and frequentists.

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Andrew Fowlie. 2021-10-29. Neyman-Pearson lemma for Bayes factors. https://doi.org/10.1080/03610926.2021.2007265

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