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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