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: 2.2
Depends: R (≥ 2.10), Matrix
Imports: methods, utils, reliaR
Suggests: Rmosek, knitr, digest
Published: 2020-01-22
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
CRAN checks: REBayes results

Downloads:

Reference manual: REBayes.pdf
Vignettes: Bayesian Deconvolution
MEDDE: Penalized Renyi Density Estimation
REBayes: Empirical Bayes for Mixtures
Package source: REBayes_2.2.tar.gz
Windows binaries: r-devel: not available, r-release: REBayes_2.2.zip, r-oldrel: not available
macOS binaries: r-release: REBayes_2.2.tgz, r-oldrel: REBayes_2.2.tgz
Old sources: REBayes archive

Reverse dependencies:

Reverse suggests: ashr, mixsqp

Linking:

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