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

Implements the expectation-maximization (EM) algorithm as described in Fiksel et al. (2020) <arXiv:2004.07881> for transformation-free linear regression for compositional outcomes and predictors.

Version: 0.1.0
Imports: SQUAREM (≥ 2020.3), future, future.apply
Suggests: knitr, ggtern, gtools, remotes, testthat, markdown
Published: 2020-06-25
Author: Jacob Fiksel ORCID iD [aut, cre], Abhirup Datta [ctb]
Maintainer: Jacob Fiksel <jfiksel at>
License: GPL-2
NeedsCompilation: no
Materials: README NEWS
CRAN checks: codalm results


Reference manual: codalm.pdf
Vignettes: How to use codalm
Package source: codalm_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: codalm_0.1.0.tgz, r-oldrel: codalm_0.1.0.tgz

Reverse dependencies:

Reverse imports: Compositional


Please use the canonical form to link to this page.