ordinalbayes: Bayesian Ordinal Regression for High-Dimensional Data

Provides a function for fitting various penalized Bayesian cumulative link ordinal response models when the number of parameters exceeds the sample size. These models have been described in Zhang and Archer (2021) <doi:10.1186/s12859-021-04432-w>.

Version: 0.1.1
Depends: DESeq2, R (≥ 2.10), SummarizedExperiment
Imports: coda, devtools, dclone, runjags
Suggests: knitr, Biobase, testthat (≥ 3.0.0), rmarkdown
Published: 2022-04-06
Author: Kellie J. Archer ORCID iD [aut, cre], Anna Seffernick [ctb], Shuai Sun [ctb], Yiran Zhang [aut]
Maintainer: Kellie J. Archer <archer.43 at osu.edu>
BugReports: https://github.com/kelliejarcher/ordinalbayes/issues
License: MIT + file LICENSE
URL: https://github.com/kelliejarcher/ordinalbayes
NeedsCompilation: no
SystemRequirements: JAGS (>= 4.0.0)
Citation: ordinalbayes citation info
Materials: README
CRAN checks: ordinalbayes results

Documentation:

Reference manual: ordinalbayes.pdf
Vignettes: ordinalbayes: Bayesian Ordinal Regression for High-Dimensional Data

Downloads:

Package source: ordinalbayes_0.1.1.tar.gz
Windows binaries: r-devel: ordinalbayes_0.1.1.zip, r-release: ordinalbayes_0.1.1.zip, r-oldrel: ordinalbayes_0.1.1.zip
macOS binaries: r-release (arm64): ordinalbayes_0.1.1.tgz, r-oldrel (arm64): ordinalbayes_0.1.1.tgz, r-release (x86_64): ordinalbayes_0.1.1.tgz
Old sources: ordinalbayes archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ordinalbayes to link to this page.