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) .


ordinalbayes

Installing ordinalbayes

  1. Install JAGS https://mcmc-jags.sourceforge.io
  2. Install R https://cran.r-project.org
  3. Install runjags which is hosted on CRAN and http://runjags.sourceforge.net
  4. Install Bioconductor packages a. See https://www.bioconductor.org/install/ to install base Bioconductor packages b. To run examples using finalSet and reducedSet the DESeq2 package is needed. To install run

    BiocManager::install("DESeq2")

  5. Install ordinalbayes using a. within R use > install.packages("ordinalbayes") or b. > devtools::install_github("kelliejarcher/ordinalbayes", build_vignettes = TRUE) This latter command takes longer because the vignette needs to be built.

Reference manual

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install.packages("ordinalbayes")

0.1.2 by Kellie J. Archer, a year ago


https://github.com/kelliejarcher/ordinalbayes


Report a bug at https://github.com/kelliejarcher/ordinalbayes/issues


Browse source code at https://github.com/cran/ordinalbayes


Authors: Kellie J. Archer [aut, cre] (ORCID: , Anna Seffernick [ctb] , Shuai Sun [ctb] , Yiran Zhang [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports coda, dclone, runjags

Depends on DESeq2, SummarizedExperiment

Suggests knitr, Biobase, testthat, rmarkdown

System requirements: JAGS (>= 4.0.0)


See at CRAN