Filzmoser, P., & Hron, K. (2020). Compositional Data Analysis in Chemometrics. In R. Tauler, B. Walczak, & S. Brown (Eds.), Comprehensive Chemometrics. Chemical and Biochemical Data Analysis (pp. 641–662). Elsevier. https://doi.org/10.1016/B978-0-12-409547-2.14591-3
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Buchtitel:
Comprehensive Chemometrics. Chemical and Biochemical Data Analysis
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Zugehörige Publikation(en):
Comprehensive Chemometrics. Chemical and Biochemical Data Analysis
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Zusammenfassung:
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.
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Stichwörter:
Aitchison geometryBootstrapClassificationCompositional dataLinear discriminant analysisPartial least squaresPLS-DAPrincipal component analysisRegressionRelative informationValidation
