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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 MCMC. Also see Tak et al. (2019) <doi:10.1080/10618600.2019.1704295>.
| Version: | 1.0.1 |
| Depends: | R (≥ 2.2.0) |
| Imports: | MCMCpack (≥ 1.4-4), mvtnorm (≥ 1.0-11), Rdpack, stats |
| Published: | 2024-01-27 |
| 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_1.0.1.tar.gz |
| Windows binaries: | r-devel: Rdta_1.0.1.zip, r-release: Rdta_1.0.1.zip, r-oldrel: Rdta_1.0.1.zip |
| macOS binaries: | r-release (arm64): Rdta_1.0.1.tgz, r-oldrel (arm64): Rdta_1.0.1.tgz, r-release (x86_64): Rdta_1.0.1.tgz, r-oldrel (x86_64): Rdta_1.0.1.tgz |
| Old sources: | Rdta archive |
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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.