Package: easyCODA 0.40.2
easyCODA: Compositional Data Analysis in Practice
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.
Authors:
easyCODA_0.40.2.tar.gz
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easyCODA_0.40.2.tgz(r-4.4-any)easyCODA_0.40.2.tgz(r-4.3-any)
easyCODA_0.40.2.tar.gz(r-4.5-noble)easyCODA_0.40.2.tar.gz(r-4.4-noble)
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easyCODA.pdf |easyCODA.html✨
easyCODA/json (API)
# Install 'easyCODA' in R: |
install.packages('easyCODA', repos = c('https://michaelgreenacre.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/michaelgreenacre/codainpractice/issues
Last updated 3 months agofrom:3a9ea3953d. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 27 2024 |
R-4.5-win | OK | Oct 27 2024 |
R-4.5-linux | OK | Oct 27 2024 |
R-4.4-win | OK | Oct 27 2024 |
R-4.4-mac | OK | Oct 27 2024 |
R-4.3-win | OK | Oct 27 2024 |
R-4.3-mac | OK | Oct 27 2024 |
Exports:ACLUSTALRBARCACIplot_bivCLOSECLRDOTDUMMYFINDALRILRinvALRinvCLRinvSLRLRLR.VARLRAPCAPLOT.CAPLOT.LRAPLOT.PCAPLOT.RDAPLRRDASLRSTEPSTEPRVARWARD
Dependencies:caclusterellipselatticeMASSMatrixmgcvnlmepermutevegan