Datensatz Zitierlink: 
http://hdl.handle.net/20.500.12708/30121
-
Titel: 
Compositional Data Analysis in Chemometrics
en
Zitat: 
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
-
Verlags-DOI: 
10.1016/B978-0-12-409547-2.14591-3
-
Publikationstyp: 
Buchbeitrag - Beitrag in Sammelband
de
Autor_innen: 
Filzmoser, Peter 
Hron, Karel 
-
Organisations­einheit: 
E105-06 - Forschungsbereich Computational Statistics 
-
Erschienen in: 
Comprehensive Chemometrics. Chemical and Biochemical Data Analysis 
-
ISBN: 
978-0-444-64166-3
-
Datum (veröffentlicht): 
2020
-
Umfang: 
22
-
Verlag: 
Elsevier
-
Peer Reviewed: 
Ja
-
Keywords: 
Aitchison geometryBootstrapClassificationCompositional dataLinear discriminant analysisPartial least squaresPLS-DAPrincipal component analysisRegressionRelative informationValidation
-
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.
en
Weitere Information: 
Public link: https://www.elsevier.com/books/comprehensive-chemometrics/brown/978-0-444-64165-6
-
Forschungs­schwerpunkte: 
Computational Materials Science: 100%
-
Wissenschafts­zweig: 
Mathematik
Informatik
-
Enthalten in den Sammlungen:
Book Contribution

Zur Langanzeige

Seiten Aufrufe

281
aufgerufen am 01.12.2023

Google ScholarTM

Check