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Univariate and multivariate methods for compositional data analysis, based on logratios. The package implements the approach in the book Compositional Data Analysis in Practice by Michael Greenacre (2018), where accent is given to simple pairwise logratios. Selection can be made of logratios that account for a maximum percentage of logratio variance. Various multivariate analyses of logratios are included in the package.
Version: | 0.40.2 |
Depends: | R (≥ 2.10) |
Imports: | ca (≥ 0.7), vegan (≥ 2.3), ellipse (≥ 0.4.1) |
Published: | 2024-08-27 |
DOI: | 10.32614/CRAN.package.easyCODA |
Author: | Michael Greenacre [aut, cre] |
Maintainer: | Michael Greenacre <michael.greenacre at upf.edu> |
License: | GPL-2 | GPL-3 [expanded from: GPL] |
URL: | https://github.com/michaelgreenacre/CODAinPractice/ |
NeedsCompilation: | no |
Citation: | easyCODA citation info |
CRAN checks: | easyCODA results |
Reference manual: | easyCODA.pdf |
Package source: | easyCODA_0.40.2.tar.gz |
Windows binaries: | r-devel: easyCODA_0.40.2.zip, r-release: easyCODA_0.40.2.zip, r-oldrel: easyCODA_0.40.2.zip |
macOS binaries: | r-release (arm64): easyCODA_0.40.2.tgz, r-oldrel (arm64): easyCODA_0.40.2.tgz, r-release (x86_64): easyCODA_0.40.2.tgz, r-oldrel (x86_64): easyCODA_0.40.2.tgz |
Old sources: | easyCODA archive |
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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.