Contributions to Books:
P. Filzmoser, K. Hron:
"Compositional Data analysis in chemometrics, In R. Tauler, B. Walczak and S.D. Brown, editors.";
in: "Comprehensive Chemometrics: Chemical and Biochemical Data Analysis",
2;
R. Tauler, B. Walczak, S.D. Brown (ed.);
Elsevier,
2020,
ISBN: 9780444641656,
641
- 662.
English abstract:
This article presents an introduction to the field and methods of compositional data analysis. The basic concepts and ideas are explained, and the approach is motivated from a geometrical perspective. Multivariate methods that are relevant in chemometrics are considered from the point of view of compositional data analysis, such as principal component analysis, multivariate outlier detection, as well as regression and classification, also for the high-dimensional case. The article includes several examples which illustrate the use of this methodology for practical data analysis.
Keywords:
Aitchison geometryBootstrapClassificationCompositional dataLinear discriminant analysisPartial least squaresPLS-DAPrincipal component analysisRegressionRelative informationValidation
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.1016/B978-0-12-409547-2.14591-3
Electronic version of the publication:
https://www.sciencedirect.com/science/article/pii/B9780124095472145913?via%3Dihub
Created from the Publication Database of the Vienna University of Technology.