corncob: Count Regression for Correlated Observations with the Beta-Binomial

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: 0.4.1
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: 2024-01-10
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 <adwillis at uw.edu>
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

Documentation:

Reference manual: corncob.pdf
Vignettes: Introduction to corncob, no phyloseq
Introduction to corncob

Downloads:

Package source: corncob_0.4.1.tar.gz
Windows binaries: r-devel: corncob_0.4.1.zip, r-release: corncob_0.4.1.zip, r-oldrel: corncob_0.4.1.zip
macOS binaries: r-release (arm64): corncob_0.4.1.tgz, r-oldrel (arm64): corncob_0.4.1.tgz, r-release (x86_64): corncob_0.4.1.tgz
Old sources: corncob archive

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