Provides joint analysis and imputation of linear regression models, generalized linear regression models or linear mixed models with incomplete (covariate) data in the Bayesian framework. The package performs some preprocessing of the data and creates a 'JAGS' model, which will then automatically be passed to 'JAGS' <http://mcmc-jags.sourceforge.net> with the help of the package 'rjags'. It also provides summary and plotting functions for the output.
| Version: | 0.2.0 |
| Depends: | rjags (≥ 4-6) |
| Imports: | MASS, mcmcse, coda |
| Suggests: | knitr, rmarkdown, mice, foreign |
| Published: | 2018-07-05 |
| Author: | Nicole S. Erler [aut, cre] |
| Maintainer: | Nicole S. Erler <n.erler at erasmusmc.nl> |
| BugReports: | https://github.com/nerler/JointAI |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/nerler/JointAI |
| NeedsCompilation: | no |
| SystemRequirements: | JAGS (http://mcmc-jags.sourceforge.net) |
| Materials: | README NEWS |
| CRAN checks: | JointAI results |
| Reference manual: | JointAI.pdf |
| Package source: | JointAI_0.2.0.tar.gz |
| Windows binaries: | r-devel: JointAI_0.2.0.zip, r-release: JointAI_0.2.0.zip, r-oldrel: JointAI_0.2.0.zip |
| OS X binaries: | r-release: JointAI_0.2.0.tgz, r-oldrel: JointAI_0.2.0.tgz |
| Old sources: | JointAI archive |
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