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: 1.0.0
Depends: R (≥ 4.0), optimParallel
Imports: dplyr, ggplot2, moments, mvtnorm, nlme, numDeriv, purrr, ggrepel, furrr, future, haven
Published: 2021-09-18
Author: Fernanda L. Schumacher ORCID iD [aut, cre], Larissa A. Matos ORCID iD [aut], Victor H. Lachos ORCID iD [aut]
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: Robust
CRAN checks: skewlmm results

Documentation:

Reference manual: skewlmm.pdf

Downloads:

Package source: skewlmm_1.0.0.tar.gz
Windows binaries: r-devel: skewlmm_1.0.0.zip, r-release: skewlmm_1.0.0.zip, r-oldrel: skewlmm_1.0.0.zip
macOS binaries: r-release (arm64): skewlmm_1.0.0.tgz, r-release (x86_64): skewlmm_1.0.0.tgz, r-oldrel: skewlmm_1.0.0.tgz
Old sources: skewlmm archive

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