Applied compositional data analysis. With worked examples in R

Abstract

The theoretical concepts explained in the book are illustrated by examples which make use of the statistical software environment R. In this chapter, a brief introduction to some functionalities of R is given. This introduction does not replace a general introduction to R, but it provides the background that is necessary to understand the examples and the R code in the book.

The methods explained in this book are exclusively available in the R package robCompositions. The package includes methods for the analysis of compositional data including robust methods, algorithms for the imputation of missing values, methods to replace rounded zeros, outlier detection for compositional data, (robust) principal component analysis for compositional data, (robust) discriminant analysis for compositional data (Fisher rule), robust regression with compositional predictors, (robust) Anderson-Darling normality tests for compositional data, as well as functions to express compositional data in coordinates.