Compositional Data Analysis

Correlation Analysis for Compositional Data

Compositional data need a special treatment prior to correlation analysis. In this paper we argue why standard transformations for compositional data are not suitable for computing correlations, and why the use of raw or log-transformed data is neither meaningful. As a solution, a procedure based on balances is outlined, leading to sensible correlation measures. The construction of the balances...

A Concise Guide to Compositional Data Analysis

Robust factor analysis for compositional data

Factor analysis as a dimension reduction technique is widely used with compositional data. Using the method for raw data or for improperly transformed data will, however, lead to biased results and consequently to misleading interpretations. Although some procedures, suitable for factor analysis with compositional data, were already developed, they require pre-knowledge of variable groups, or a...

Lecture Notes on Compositional Data Analysis

Preface These notes have been prepared as support to a short course on compositional data analysis. Their aim is to transmit the basic concepts and skills for simple applications, thus setting the premises for more advanced projects. One should be aware that frequent updates will be required in the near future, as the theory presented here is a field of active research. The notes are based both...

Clustering compositional data trajectories

This work is motivated by the following question: given a sample of compositional data trajectories (i.e. sequences of composition measurements along a domain), how can one propose a segmentation procedure leading to homogeneous classes? In other words, our contribution aims at studying statistical methods suited for clustering compositional data, when the observations are constituted by trajec...