Interpolative biplots applied to principal component analysis and canonical correlation analysis

• Type: Article in International Scientific Journal
• Date: 2003

Authors

Alves, MR (Author) Other; Oliveira, MB (Author) FFUP

Journal

Title: Journal of Chemometrics

Vol. 17

Pages: 594-602

ISSN: 0886-9383

Publisher: Wiley-Blackwell

Indexing

ISI Web of Knowledge - 7 Citations

Scopus - 12 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-000-EMC

DOI: 10.1002/cem.827

Abstract (EN): The multivariate statistical analysis of cis and trans isomers of fatty acid profiles of eight margarine brands obtained by HRGC/FID/capillary column was carried out based on biplots applied to principal component analysis (PCA) and canonical correlation analysis (CCA). It is shown that while predictive biplots are the best choice for interpretation purposes, interpolative biplots are very useful for classification of new observations that were not used for the construction of the principal component or canonical dimension axes. Copyright (C) 2004 John Wiley Sons, Ltd.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9