codalm: Transformation-Free Linear Regression for Compositional Outcomes and Predictors

Implements the expectation-maximization (EM) algorithm as described in Fiksel et al. (2022) <doi:10.1111/biom.13465> for transformation-free linear regression for compositional outcomes and predictors.

Version: 0.1.3
Imports: SQUAREM (≥ 2020.3), future, future.apply
Suggests: knitr, gtools, remotes, testthat, rmarkdown, ggtern, ggplot2
Published: 2025-12-11
DOI: 10.32614/CRAN.package.codalm
Author: Jacob Fiksel ORCID iD [aut], Abhirup Datta [ctb], Sandipan Pramanik ORCID iD [cre, ctb]
Maintainer: Sandipan Pramanik <sandy.pramanik at gmail.com>
BugReports: https://github.com/jfiksel/codalm/issues
License: GPL-2
URL: https://github.com/jfiksel/codalm
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: codalm results

Documentation:

Reference manual: codalm.html , codalm.pdf
Vignettes: How to use codalm (source, R code)

Downloads:

Package source: codalm_0.1.3.tar.gz
Windows binaries: r-devel: codalm_0.1.3.zip, r-release: codalm_0.1.2.zip, r-oldrel: codalm_0.1.3.zip
macOS binaries: r-release (arm64): codalm_0.1.3.tgz, r-oldrel (arm64): codalm_0.1.3.tgz, r-release (x86_64): codalm_0.1.3.tgz, r-oldrel (x86_64): codalm_0.1.3.tgz
Old sources: codalm archive

Reverse dependencies:

Reverse suggests: Compositional

Linking:

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