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

Implements the expectation-maximization (EM) algorithm as described in Fiksel et al. (2021) <doi:10.1111/biom.13465> for transformation-free linear regression for compositional outcomes and predictors.

Version: 0.1.2
Depends: R (≥ 2.10)
Imports: SQUAREM (≥ 2020.3), future, future.apply
Suggests: knitr, gtools, remotes, testthat, rmarkdown
Published: 2021-07-26
DOI: 10.32614/CRAN.package.codalm
Author: Jacob Fiksel ORCID iD [aut, cre], Abhirup Datta [aut]
Maintainer: Jacob Fiksel <jfiksel 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.pdf
Vignettes: How to use codalm

Downloads:

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

Reverse dependencies:

Reverse suggests: Compositional

Linking:

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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