Compositional data analysis -- linear algebra, visualization and interpretation

2021/10/24 by Michael Greenacre, Greenacre, Michael
Computer Science · Engineering · #FOS: Computer and information sciences #Geochemistry and Geologic Mapping #Hydrocarbon exploration and reservoir analysis #Methodology (stat.ME)

paper · pdf · doi:10.48550/arxiv.2110.12439

openalex publication_date 2021/10/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Compositional data analysis is concerned with multivariate data that have a constant sum, usually 1 or 100%. These are data often found in biochemistry and geochemistry, but also in the social sciences, when relative values are of interest rather than the raw values. Recent applications are in the area of very high-dimensional "omics" data. Logratios are frequently used for this type of data, i.e. the logarithms of ratios of the components of the data vectors. These ratios raise interesting issues in matrix-vector representation, computation and interpretation, which will be dealt with in this chapter.

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