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Empirical Bayes Deconvolution
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--- output: github_document --- <!-- README.md is generated from the source: README.Rmd --> # Empirical Bayes Deconvolution [![Travis-CI Build Status](https://travis-ci.org/bnaras/deconvolveR.svg?branch=master)](https://travis-ci.org/bnaras/deconvolveR) [![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/deconvolveR)](https://cran.r-project.org/package=deconvolveR) [![Coverage Status](https://img.shields.io/codecov/c/github/bnaras/deconvolveR/master.svg)](https://codecov.io/github/bnaras/deconvolveR?branch=master) 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") ```