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.