blme: Bayesian Linear Mixed-Effects Models

Maximum a posteriori estimation for linear and generalized linear mixed-effects models in a Bayesian setting, implementing the methods of Chung, et al. (2013) <doi:10.1007/s11336-013-9328-2>. Extends package 'lme4' (Bates, Maechler, Bolker, and Walker (2015) <doi:10.18637/jss.v067.i01>).

Version: 1.0-5
Depends: R (≥ 3.0-0), lme4 (≥ 1.0-6)
Imports: methods, stats, utils
Suggests: expint (≥ 0.1-3), testthat
Published: 2021-01-05
DOI: 10.32614/CRAN.package.blme
Author: Vincent Dorie ORCID iD [aut, cre], Douglas Bates ORCID iD [ctb] (lme4 non-modular functions), Martin Maechler ORCID iD [ctb] (lme4 non-modular functions), Ben Bolker ORCID iD [ctb] (lme4 non-modular functions), Steven Walker ORCID iD [ctb] (lme4 non-modular functions)
Maintainer: Vincent Dorie <vdorie at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: blme citation info
Materials: ChangeLog
In views: MixedModels
CRAN checks: blme results


Reference manual: blme.pdf


Package source: blme_1.0-5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): blme_1.0-5.tgz, r-oldrel (arm64): blme_1.0-5.tgz, r-release (x86_64): blme_1.0-5.tgz, r-oldrel (x86_64): blme_1.0-5.tgz
Old sources: blme archive

Reverse dependencies:

Reverse depends: brxx, eirm
Reverse imports: merTools, muscat, phoenics
Reverse suggests: glmmTMB, insight, marginaleffects, MAST, miceadds, parameters


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