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easyCODA (version 0.40.2)

Compositional Data Analysis in Practice

Description

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.

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Install

install.packages('easyCODA')

Monthly Downloads

341

Version

0.40.2

License

GPL

Issues

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Maintainer

Michael Greenacre

Last Published

August 27th, 2024

Functions in easyCODA (0.40.2)

PLOT.PCA

Plot the results of a principal component analysis
ALR

Additive logratios
PLOT.CA

Plot the results of a correspondence analysis
PCA

Principal component analysis
fish

Dataset: FishMorphology
invALR

Inverse of additive logratios
ACLUST

Amalgamation clustering of the parts of a compositional data matrix
LR

All pairwise logratios
veg

Dataset: Vegetables
SLR

Amalgamation (summed) logratio
time

Dataset: TimeBudget
PLR

Pivot logratios
easyCODA-package

tools:::Rd_package_title("easyCODA")
WARD

Ward clustering of a compositional data matrix
VAR

Variance of a vector of observations, dividing by n rather than n-1
cups

Dataset: RomanCups
STEPR

Stepwise selection of pairwise logratios for generalized linear modelling
invCLR

Inverse of centred logratios
invSLR

Inverse of full set of amalgamation balances
CLOSE

Closure of rows of compositional data matrix
DOT

Dot plot
CIplot_biv

Bivariate confidence and data ellipses
FINDALR

Find the best ALR transformation
DUMMY

Dummy variable (indicator) coding
CLR

Centred logratios
CA

Correspondence analysis
BAR

Compositional bar plot
LR.VAR

Total logratio variance
ILR

Isometric logratio
PLOT.RDA

Plot the results of a redundancy analysis
PLOT.LRA

Plot the results of a logratio analysis
STEP

Stepwise selection of logratios
RDA

Redundancy analysis
LRA

Logratio analysis