Rdta: Data Transforming Augmentation for Linear Mixed Models
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 |
| DOI: |
10.32614/CRAN.package.Rdta |
| 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 |
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