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codaredistlm: Compositional Data Linear Models with Composition Redistribution

Provided data containing an outcome variable, compositional variables and additional covariates (optional); linearly regress the outcome variable on an isometric log ratio (ilr) transformation of the linearly dependent compositional variables. The package provides predictions (with confidence intervals) in the change (delta) in the outcome/response variable based on the multiple linear regression model and evenly spaced reallocations of the compositional values. The compositional data analysis approach implemented is outlined in Dumuid et al. (2017a) <doi:10.1177/0962280217710835> and Dumuid et al. (2017b) <doi:10.1177/0962280217737805>.

Version: 0.1.0
Imports: compositions, ggplot2, broom, knitr
Suggests: testthat
Published: 2022-12-22
DOI: 10.32614/CRAN.package.codaredistlm
Author: Ty Stanford ORCID iD [aut, cre], Charlotte Lund Rasmussen ORCID iD [aut], Dot Dumuid ORCID iD [aut]
Maintainer: Ty Stanford <tystan at gmail.com>
BugReports: https://github.com/tystan/codaredistlm/issues
License: GPL-2
URL: https://github.com/tystan/codaredistlm
NeedsCompilation: no
Materials: README
CRAN checks: codaredistlm results

Documentation:

Reference manual: codaredistlm.pdf

Downloads:

Package source: codaredistlm_0.1.0.tar.gz
Windows binaries: r-devel: codaredistlm_0.1.0.zip, r-release: codaredistlm_0.1.0.zip, r-oldrel: codaredistlm_0.1.0.zip
macOS binaries: r-release (arm64): codaredistlm_0.1.0.tgz, r-oldrel (arm64): codaredistlm_0.1.0.tgz, r-release (x86_64): codaredistlm_0.1.0.tgz, r-oldrel (x86_64): codaredistlm_0.1.0.tgz

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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.