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: 1.3
Depends: R (≥ 2.10), Matrix
Imports: Rmosek, methods, reliaR
Suggests: knitr, digest
Published: 2018-02-14
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 for use of Rmosek, optional use of the pogs optimizer may require CUDA/GPU accoutrements.
Citation: REBayes citation info
Materials: ChangeLog
CRAN checks: REBayes results


Reference manual: REBayes.pdf
Vignettes: Bayesian Deconvolution
MEDDE: Penalized Renyi Density Estimation
REBayes: Empirical Bayes for Mixtures
Package source: REBayes_1.3.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
OS X El Capitan binaries: r-release: not available
OS X Mavericks binaries: r-oldrel: not available
Old sources: REBayes archive

Reverse dependencies:

Reverse suggests: ashr


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