doi:10.1214/19-AOAS1283>. It allows for both mean and overdispersion covariates.">

corncob: Count Regression for Correlated Observations with the Beta-Binomial (original) (raw)

Statistical modeling for correlated count data using the beta-binomial distribution, described in Martin et al. (2020) <doi:10.1214/19-AOAS1283>. It allows for both mean and overdispersion covariates.

Version:

0.4.2

Depends:

R (≥ 3.2)

Imports:

stats, utils, VGAM, numDeriv, ggplot2, trust, dplyr, magrittr, detectseparation, scales, rlang

Suggests:

knitr, rmarkdown, testthat, covr, limma, slam, R.rsp, optimx, phyloseq

Published:

2025-03-29

DOI:

10.32614/CRAN.package.corncob

Author:

Bryan D Martin [aut], Daniela Witten [aut], Sarah Teichman [ctb], Amy D Willis [aut, cre], Thomas W Yee [ctb] (VGAM library), Xiangjie Xue [ctb] (VGAM library)

Maintainer:

Amy D Willis

BugReports:

https://github.com/statdivlab/corncob/issues

License:

GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]

URL:

https://github.com/statdivlab/corncob,https://statdivlab.github.io/corncob/

NeedsCompilation:

no

Materials:

README

CRAN checks:

corncob results