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Empirical Bayes Deconvolution

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An unknown prior density \(g(\theta)\) has yielded (unobservable) \(\Theta_1, \Theta_2,\ldots,\Theta_N\), and each \(\Theta_i\) produces an observation \(X_i\) from an exponential family. deconvolveR is an R package for estimating prior distribution \(g(\theta)\) from the data using Empirical Bayes deconvolution.

Details and examples may be found in the paper by Narasimhan and Efron, 2020. A vignette with further examples is also provided.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.