Compositional Data Analysis in Practice

2. Auflage 2026
ISBN: 978-1-041-23076-2
Verlag: CRC Press

Buch, Englisch, 208 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Chapman & Hall/CRC Interdisciplinary Statistics

“This book would make for a wonderful one semester course in applied multivariate statistics, suitable for upper-level undergraduates who are masters students in data science.”
~Trevor Hastie, The John A. Overdeck Professor, Professor of Statistics and Biomedical Data Science (emeritus), Stanford University, USA

“This book is a small gem that will find its place among those who are interested in learning about this important topic from a master of clarity and exposition…Graduate students and applied researchers, across the quantitative sciences who encounter proportional data, will find this an authoritative yet accessible guide.”
~Michael Friendly, York University, Canada

“This book is an inspiring text for applied scientists and graduate students with backgrounds in multivariate analysis and are interested in mastering the analysis of compositional data.”
~Jan Graffelman, Professor, Technical University of Catalonia, Spain

Compositional data – proportions, percentages, and any data that sum to a constant – appear across virtually every scientific discipline, from geochemistry and ecology to political science and genomics. This thoroughly revised and extended second edition continues to provide a simple and accessible treatment of compositional data analysis (CoDA) in a pedagogical format.

Key Features of the Second Edition:

- 60% more material than the first edition

- Additional chapters on weighting of compositional parts, the analysis of complete compositions, the analysis of shape, high-dimensional genomic compositions, as well as two more case studies

- Practical, example-driven approach, using 13 different data sets across different disciplines

- Unique eight-pages-per-chapter format to facilitate both self-study and teaching of the subject

- Revision of the easyCODA R package to include new features such as amalgamation clustering and variable selection in unsupervised and supervised learning

The book is a valuable resource for practitioners in all applied areas where compositional data are encountered, including bio- and geochemistry, food research, genomics, ecology, linguistics, marketing, financial budgets in economics, and time-use in behavioural research and epidemiology.

Zielgruppe

Academic, Postgraduate, and Professional Reference

Autoren/Hrsg.

Greenacre, Michael

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsstatistik, Demographie

Inhaltsverzeichnis

1. What are compositional data, and why are they special?. 2. Geometry and visualization of compositional data. 3. Logratio transformations. 4. Properties and distributions of logratios. 5. Clustering of compositional data. 6. Dimension reduction using logratio analysis. 7. Regression models involving compositional data. 8. The zeros problem, with some solutions. 9. Variable selection for unsupervised and supervised learning. 10. To weight or not to weight. 11. The analysis of complete compositions. 12. The analysis of shape. 13. High-dimensional “omics” data. 14. Case study 1: Fatty acid compositions of marine amphipods. 15. Case study 2: Sedimentological modelling with compositional predictors. 16. Case study 3: Ecological modeling with compositional responses.

Über Autor(innen)

Michael Greenacre is “Professor Talent Superior” in the Department of Economics and Business of the Universitat Pompeu Fabra, Barcelona, where he has worked for 31 years until his recent retirement. He has written over 100 research articles, as well as eight books, including three editions of Correspondence Analysis in Practice (1993, 2007, 2016), which has been translated into Spanish and Japanese. He has also edited four books with Jörg Blasius of Bonn University, on correspondence analysis and related methods. He continues to work and publish actively in correspondence analysis and compositional data analysis, in collaboration with researchers in several countries, in the fields of biochemistry, geochemistry, archaeology, genomics and ecology, with a recent new interest in sensometrics (statistics of sensory data). He is also a musician and composer, and has published two albums of his own compositions, “You, Woman” and “Below the Surface”, with the singer Gurdeep Stephens and guitarist Santi Careta, and has a popular YouTube channel of his satirical statistical songs.