Sammanfattning
Compositional data represent a specific family of multivariate data, where the information of interest is contained in the ratios between parts rather than in absolute values of single parts. The analysis of such specific data is challenging as the application of standard multivariate analysis tools on the raw observations can lead to spurious results. Hence, it is appropriate to apply certain transformations prior to further analysis. One popular multivariate data analysis tool is independent component analysis. Independent component analysis aims to find statistically independent components in the data and as such might be seen as an extension to principal component analysis. In this paper, we examine an approach of how to apply independent component analysis on compositional data by respecting the nature of the latter and demonstrate the usefulness of this procedure on a metabolomics dataset.
| Originalspråk | engelska |
|---|---|
| Titel på värdpublikation | Advances in Contemporary Statistics and Econometrics : Festschrift in Honor of Christine Thomas-Agnan |
| Redaktörer | Abdelaati Daouia, Anne Ruiz-Gazen |
| Antal sidor | 21 |
| Utgivningsort | Cham |
| Förlag | Springer |
| Utgivningsdatum | 2021 |
| Sidor | 525-545 |
| ISBN (tryckt) | 978-3-030-73248-6, 978-3-030-73251-6 |
| ISBN (elektroniskt) | 978-3-030-73249-3 |
| DOI | |
| Status | Publicerad - 2021 |
| Externt publicerad | Ja |
| MoE-publikationstyp | A3 Del av bok eller annan forskningsbok |
Bibliografisk information
Publisher Copyright:© Springer Nature Switzerland AG 2021.
Vetenskapsgrenar
- 112 Statistik
- 113 Data- och informationsvetenskap