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.