BayesRGMM: Bayesian Robust Generalized Mixed Models for Longitudinal Data
To perform model estimation using MCMC algorithms with Bayesian methods for incomplete longitudinal studies on binary and ordinal outcomes that are measured repeatedly on subjects over time with drop-outs. Details about the method can be found in the vignette or <https://sites.google.com/view/kuojunglee/r-packages/bayesrgmm>.
| Version: | 2.2 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rcpp (≥ 1.0.1), MASS, batchmeans, abind, reshape, msm, mvtnorm, plyr, Rdpack |
| LinkingTo: | Rcpp, RcppArmadillo, RcppDist |
| Suggests: | testthat |
| Published: | 2022-05-10 |
| DOI: | 10.32614/CRAN.package.BayesRGMM |
| Author: | Kuo-Jung Lee 
[aut, cre],
Hsing-Ming Chang [ctb],
Ray-Bing Chen [ctb],
Keunbaik Lee [ctb],
Chanmin Kim [ctb] |
| Maintainer: | Kuo-Jung Lee <kuojunglee at ncku.edu.tw> |
| License: | GPL-2 |
| URL: | https://sites.google.com/view/kuojunglee/r-packages |
| NeedsCompilation: | yes |
| CRAN checks: | BayesRGMM results |
Documentation:
| Reference manual: | BayesRGMM.pdf |
| Vignettes: |
Bayesian Robust Generalized Mixed Models for Longitudinal Data (source, R code) |
Downloads:
| Package source: | BayesRGMM_2.2.tar.gz |
| Windows binaries: | r-devel: BayesRGMM_2.2.zip, r-release: BayesRGMM_2.2.zip, r-oldrel: BayesRGMM_2.2.zip |
| macOS binaries: | r-devel (arm64): BayesRGMM_2.2.tgz, r-release (arm64): BayesRGMM_2.2.tgz, r-oldrel (arm64): BayesRGMM_2.2.tgz, r-devel (x86_64): BayesRGMM_2.2.tgz, r-release (x86_64): BayesRGMM_2.2.tgz, r-oldrel (x86_64): BayesRGMM_2.2.tgz |
| Old sources: | BayesRGMM archive |
Linking:
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