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Empirical Bayes Deconvolution
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README.Rmd

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output: github_document
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<!-- 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")
```



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