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cAIC4: Conditional Akaike Information Criterion for 'lme4' and 'nlme'

Provides functions for the estimation of the conditional Akaike information in generalized mixed-effect models fitted with (g)lmer() from 'lme4', lme() from 'nlme' and gamm() from 'mgcv'. For a manual on how to use 'cAIC4', see Saefken et al. (2021) <doi:10.18637/jss.v099.i08>.

Version: 1.0
Depends: lme4 (≥ 1.1-6), methods, Matrix, stats4, nlme
Imports: RLRsim, mgcv, mvtnorm
Suggests: gamm4
Published: 2021-09-22
DOI: 10.32614/CRAN.package.cAIC4
Author: Benjamin Saefken, David Ruegamer, Philipp Baumann and Rene-Marcel Kruse, with contributions from Sonja Greven and Thomas Kneib
Maintainer: David Ruegamer <david.ruegamer at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: cAIC4 citation info
In views: MixedModels
CRAN checks: cAIC4 results

Documentation:

Reference manual: cAIC4.pdf

Downloads:

Package source: cAIC4_1.0.tar.gz
Windows binaries: r-devel: cAIC4_1.0.zip, r-release: cAIC4_1.0.zip, r-oldrel: cAIC4_1.0.zip
macOS binaries: r-release (arm64): cAIC4_1.0.tgz, r-oldrel (arm64): cAIC4_1.0.tgz, r-release (x86_64): cAIC4_1.0.tgz, r-oldrel (x86_64): cAIC4_1.0.tgz
Old sources: cAIC4 archive

Reverse dependencies:

Reverse imports: fastFMM
Reverse suggests: parameters

Linking:

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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.