We provide a toolbox to fit univariate and multivariate linear mixed models via data transforming augmentation. Users can also fit these models via typical data augmentation for a comparison. It returns either maximum likelihood estimates of unknown model parameters (hyper-parameters) via an EM algorithm or posterior samples of those parameters via a Markov chain Monte Carlo method. Also see Tak, You, Ghosh, Su, and Kelly (2019+) <doi:10.1080/10618600.2019.1704295> <arXiv:1911.02748>.
| Version: | 1.0.0 |
| Depends: | R (≥ 2.2.0) |
| Imports: | MCMCpack (≥ 1.4-4), mvtnorm (≥ 1.0-11), Rdpack, stats |
| Published: | 2020-01-24 |
| Author: | Hyungsuk Tak, Kisung You, Sujit K. Ghosh, and Bingyue Su |
| Maintainer: | Hyungsuk Tak <hyungsuk.tak at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | Rdta results |
| Reference manual: | Rdta.pdf |
| Package source: | Rdta_1.0.0.tar.gz |
| Windows binaries: | r-devel: Rdta_1.0.0.zip, r-release: Rdta_1.0.0.zip, r-oldrel: Rdta_1.0.0.zip |
| macOS binaries: | r-release: Rdta_1.0.0.tgz, r-oldrel: Rdta_1.0.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=Rdta to link to this page.