Methods for analysis of compositional data including robust methods, imputation, methods to replace rounded zeros, (robust) outlier detection for compositional data, (robust) principal component analysis for compositional data, (robust) factor analysis for compositional data, (robust) discriminant analysis for compositional data (Fisher rule), robust regression with compositional predictors and (robust) AndersonDarling normality tests for compositional data as well as popular logratio transformations (addLR, cenLR, isomLR, and their inverse transformations). In addition, visualisation and diagnostic tools are implemented as well as high and lowlevel plot functions for the ternary diagram.
Package details 


Author  Matthias Templ, Karel Hron, Peter Filzmoser 
Date of publication  20170814 13:14:11 UTC 
Maintainer  Matthias Templ <matthias.templ@gmail.com> 
License  GPL (>= 2) 
Version  2.0.6 
Package repository  View on CRAN 
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