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.

The current package is still under construction but will soon appear on CRAN along with a manuscript. Meanwhile, you can reproduce many examples by installing the package in R thus:

devtools::install_github("bnaras/deconvolveR")
library(deconvolveR)
vignette("deconvolution")