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skewlmm: Scale Mixture of Skew-Normal Linear Mixed Models

It fits scale mixture of skew-normal linear mixed models using an expectation–maximization (EM) type algorithm, including some possibilities for modeling the within-subject dependence. Details can be found in Schumacher, Lachos and Matos (2021) <doi:10.1002/sim.8870>.

Version:	1.1.0
Depends:	R (≥ 4.2), optimParallel
Imports:	dplyr, furrr, future, ggplot2, ggrepel, haven, matrixcalc, methods, moments, MomTrunc, mvtnorm, nlme, numDeriv, purrr, relliptical, TruncatedNormal
Published:	2023-06-30
DOI:	10.32614/CRAN.package.skewlmm
Author:	Fernanda L. Schumacher [aut, cre], Larissa A. Matos [aut], Victor H. Lachos [aut], Katherine A. L. Valeriano [aut], Nicholas Henderson [ctb], Ravi Varadhan [ctb]
Maintainer:	Fernanda L. Schumacher <fernandalschumacher at gmail.com>
BugReports:	https://github.com/fernandalschumacher/skewlmm/issues
License:	MIT + file LICENSE
URL:	https://github.com/fernandalschumacher/skewlmm
NeedsCompilation:	no
Materials:	README NEWS
In views:	MixedModels, Robust
CRAN checks:	skewlmm results

Documentation:

Reference manual:

skewlmm.pdf

Downloads:

Package source:	skewlmm_1.1.0.tar.gz
Windows binaries:	r-devel: skewlmm_1.1.0.zip, r-release: skewlmm_1.1.0.zip, r-oldrel: skewlmm_1.1.0.zip
macOS binaries:	r-release (arm64): skewlmm_1.1.0.tgz, r-oldrel (arm64): skewlmm_1.1.0.tgz, r-release (x86_64): skewlmm_1.1.0.tgz, r-oldrel (x86_64): skewlmm_1.1.0.tgz
Old sources:	skewlmm archive

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.