REBayes: Empirical Bayes Estimation and Inference

Kiefer-Wolfowitz maximum likelihood estimation for mixture models and some other density estimation and regression methods based on convex optimization. See Koenker and Gu (2017) REBayes: An R Package for Empirical Bayes Mixture Methods, Journal of Statistical Software, 82, 1–26, <doi:10.18637/jss.v082.i08>.

Version: 2.56
Depends: R (≥ 3.5.0), Matrix
Imports: methods, utils, lattice
Suggests: Rmosek, knitr, digest
Published: 2024-06-22
DOI: 10.32614/CRAN.package.REBayes
Author: Roger Koenker [aut, cre], Jiaying Gu [ctb], Ivan Mizera [ctb]
Maintainer: Roger Koenker <rkoenker at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
SystemRequirements: MOSEK ( and MOSEK license.
Citation: REBayes citation info
Materials: ChangeLog
In views: Bayesian, Optimization
CRAN checks: REBayes results


Reference manual: REBayes.pdf
Vignettes: Bayesian Deconvolution
MEDDE: Penalized Renyi Density Estimation
REBayes: Empirical Bayes for Mixtures


Package source: REBayes_2.56.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): REBayes_2.56.tgz, r-oldrel (arm64): REBayes_2.54.tgz, r-release (x86_64): REBayes_2.56.tgz, r-oldrel (x86_64): REBayes_2.54.tgz
Old sources: REBayes archive

Reverse dependencies:

Reverse imports: RCBR
Reverse suggests: ashr, ebnm, ebTobit, mashr


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