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Empirical Bayes for the Reluctant Frequentist
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Empirical Bayes methods offer valuable tools for a large class of compound decision problems. In this tutorial we describe some basic principles of the empirical Bayes paradigm stressing their frequentist interpretation. Emphasis is placed on recent developments of nonparametric maximum likelihood methods for estimating mixture models. A more extensive introductory treatment will eventually be available in \citet{kg24}. The methods are illustrated with an extended application to models of heterogeneous income dynamics based on PSID data.
Forward citations
Cited by 2 Pith papers
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Solving Empirical Bayes via Transformers
A transformer pre-trained on synthetic Poisson data can beat the classical NPMLE estimator on several empirical Bayes tasks and run about 100x faster.
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