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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: 2.54
Depends: R (≥ 2.10), Matrix
Imports: methods, utils, lattice
Suggests: Rmosek, knitr, digest
Published: 2023-08-19
Author: Roger Koenker [aut, cre], Jiaying Gu [ctb], Ivan Mizera [ctb]
Maintainer: Roger Koenker <rkoenker at uiuc.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://www.r-project.org
NeedsCompilation: no
SystemRequirements: MOSEK (http://www.mosek.com) and MOSEK license.
Citation: REBayes citation info
Materials: ChangeLog
In views: Bayesian, Optimization
CRAN checks: REBayes results

Documentation:

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

Downloads:

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

Reverse dependencies:

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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=REBayes to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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