Compositional Data Analysis

CoDaWork, L’Escala, Spain, June 2015

  • Josep Antoni Martín-Fernández
  • Santiago Thió-Henestrosa
Conference proceedings CoDaWork 2015

Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 187)

Table of contents

  1. Front Matter
    Pages i-x
  2. J. Bergman, A. Lindahl
    Pages 1-11
  3. I. Galván-Femenía, J. Graffelman, C. Barceló-i-Vidal
    Pages 63-73
  4. G. S. Monti, G. Mateu-Figueras, V. Pawlowsky-Glahn, J. J. Egozcue
    Pages 127-143
  5. V. Pawlowsky-Glahn, T. Monreal-Pawlowsky, J. J. Egozcue
    Pages 167-180
  6. R. Tolosana-Delgado, K. G. van den Boogaart, E. Fišerová, K. Hron, I. Dunkl
    Pages 181-209

About these proceedings


The authoritative contributions gathered in this volume reflect the state of the art in compositional data analysis (CoDa). The respective chapters cover all aspects of CoDa, ranging from mathematical theory, statistical methods and techniques to its broad range of applications in geochemistry, the life sciences and other disciplines. The selected and peer-reviewed papers were originally presented at the 6th International Workshop on Compositional Data Analysis, CoDaWork 2015, held in L’Escala (Girona), Spain.

Compositional data is defined as vectors of positive components and constant sum, and, more generally, all those vectors representing parts of a whole which only carry relative information. Examples of compositional data can be found in many different fields such as geology, chemistry, economics, medicine, ecology and sociology. As most of the classical statistical techniques are incoherent on compositions, in the 1980s John Aitchison proposed the log-ratio approach to CoDa. This became the foundation of modern CoDa, which is now based on a specific geometric structure for the simplex, an appropriate representation of the sample space of compositional data.

The International Workshops on Compositional Data Analysis offer a vital discussion forum for researchers and practitioners concerned with the statistical treatment and modelling of compositional data or other constrained data sets and the interpretation of models and their applications. The goal of the workshops is to summarize and share recent developments, and to identify important lines of future research.


62Pxx, 62Hxx, 62Jxx, 62Exx compositional data multivariate statistics log-ratio approach applications in geochemistry applications in computer science applications in the life sciences geochemical data statistical modeling of compositional data log-ratio transformation constrained data CoDa

Editors and affiliations

  • Josep Antoni Martín-Fernández
    • 1
  • Santiago Thió-Henestrosa
    • 2
  1. 1.Department of Computer Science and Applied MathematicsUniversity of GironaGironaSpain
  2. 2.Department of Computer Science and Applied MathematicsUniversity of GironaGironaSpain

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