Package: codalm 0.1.1

Sandipan Pramanik

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

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

Authors:Jacob Fiksel [aut], Abhirup Datta [ctb], Sandipan Pramanik [cre, ctb]

codalm_0.1.1.tar.gz
codalm_0.1.1.zip(r-4.7-any)codalm_0.1.1.zip(r-4.6-any)codalm_0.1.1.zip(r-4.5-any)
codalm_0.1.1.tgz(r-4.6-any)codalm_0.1.1.tgz(r-4.5-any)
codalm_0.1.1.tar.gz(r-4.7-any)codalm_0.1.1.tar.gz(r-4.6-any)
codalm_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
codalm/json (API)

# Install 'codalm' in R:

install.packages('codalm', repos = c('https://jfiksel.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jfiksel/codalm/issues

On CRAN:

4.48 score 3 stars 7 scripts 405 downloads 1 mentions 3 exports 8 dependencies

Last updated from:66744ff0b3. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	128
source / vignettes	OK	162
linux-release	OK	131
macos-release	OK	159
macos-oldrel	OK	191
windows-devel	OK	84
windows-release	OK	82
windows-oldrel	OK	73
wasm-release	OK	89

Exports:codalm codalm_ci codalm_indep_test

Dependencies:codetools digest future future.apply globals listenv parallelly SQUAREM

How to use codalm

Rendered fromcodalm_quickstart.Rmdusingknitr::rmarkdown

Last update: 2025-12-10
Started: 2020-06-01

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Transformation-free Linear Regression for Compositional Outcomes and Predictors	codalm
Bootstrap Confidence Intervals Linear Regression for Compositional Outcomes and Predictors	codalm_ci
Permutation Test for Linear Independence Between Compositional Outcomes and Predictors	codalm_indep_test