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:Michael Greenacre [aut, cre]

easyCODA_0.40.2.tar.gz
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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

Datasets:
  • cups - Dataset: RomanCups
  • fish - Dataset: FishMorphology
  • time - Dataset: TimeBudget
  • veg - Dataset: Vegetables

On CRAN:

Conda:

2.26 score 1 stars 46 scripts 302 downloads 4 mentions 29 exports 10 dependencies

Last updated 7 months agofrom:3a9ea3953d. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 26 2025
R-4.5-winOKMar 26 2025
R-4.5-macOKMar 26 2025
R-4.5-linuxOKMar 26 2025
R-4.4-winOKMar 26 2025
R-4.4-macOKMar 26 2025
R-4.4-linuxOKMar 26 2025
R-4.3-winOKMar 26 2025
R-4.3-macOKMar 26 2025

Exports:ACLUSTALRBARCACIplot_bivCLOSECLRDOTDUMMYFINDALRILRinvALRinvCLRinvSLRLRLR.VARLRAPCAPLOT.CAPLOT.LRAPLOT.PCAPLOT.RDAPLRRDASLRSTEPSTEPRVARWARD

Dependencies:caclusterellipselatticeMASSMatrixmgcvnlmepermutevegan