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Canonical Correlation Analysis
Canonical Correlation Analysis (CCA) is a multivariate statistical method that identifies pairs of linear combinations — one from each of two variable sets — such that the correlation between each pair is maximised. Introduced by Harold Hotelling in his landmark 1936 Biometrika paper, CCA provides the most general linear framework for studying the association between two multivariate batteries of measurements, and many classical procedures (multiple regression, MANOVA, discriminant analysis) are special cases of it.
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Sources
- Hotelling, H. (1936). Relations between two sets of variates. Biometrika, 28(3–4), 321–377. DOI: 10.1093/biomet/28.3-4.321 ↗
- Anderson, T. W. (2003). An Introduction to Multivariate Statistical Analysis (3rd ed.). Wiley. ISBN: 978-0471360919
- Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541