It fits scale mixture of skew-normal linear mixed models using either an expectation–maximization (EM) type algorithm or its accelerated version (Damped Anderson Acceleration with Epsilon Monotonicity, DAAREM), 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: |
1.1.2 |
| Depends: |
R (≥ 4.3), optimParallel |
| Imports: |
dplyr, ggplot2, methods, stats, future, ggrepel, haven, mvtnorm, nlme, purrr, furrr, matrixcalc, moments, numDeriv, relliptical, MomTrunc, TruncatedNormal |
| Published: |
2024-12-15 |
| 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 |