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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.1 |
rolling linux/jammy R-4.5 | Rdta_1.0.1.tar.gz |
36.1 KiB |
1.0.1 |
rolling linux/noble R-4.5 | Rdta_1.0.1.tar.gz |
36.0 KiB |
1.0.1 |
rolling source/ R- | Rdta_1.0.1.tar.gz |
7.8 KiB |
1.0.1 |
latest linux/jammy R-4.5 | Rdta_1.0.1.tar.gz |
36.1 KiB |
1.0.1 |
latest linux/noble R-4.5 | Rdta_1.0.1.tar.gz |
36.0 KiB |
1.0.1 |
latest source/ R- | Rdta_1.0.1.tar.gz |
7.8 KiB |
1.0.1 |
2026-04-26 source/ R- | Rdta_1.0.1.tar.gz |
7.8 KiB |
1.0.1 |
2026-04-23 source/ R- | Rdta_1.0.1.tar.gz |
7.8 KiB |
1.0.1 |
2026-04-09 windows/windows R-4.5 | Rdta_1.0.1.zip |
38.5 KiB |
1.0.1 |
2025-04-20 source/ R- | Rdta_1.0.1.tar.gz |
7.8 KiB |