Metodbevispost

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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Taxonomisk metodpost · latent-structure / statistics

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

Öppna fullständig metod

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Relaterade metoder

Genererade från metodgrafen och visade som maskinföreslagna relationer – inga bevispåståenden härleds.

Same method familyDiscriminant Analysismachine-suggested · Relational suggestion, not evidence.See alsoFactor Analysismachine-suggested · Relational suggestion, not evidence.Used in the same domainMultiple Linear Regressionmachine-suggested · Relational suggestion, not evidence.See alsoPartial Least Squaresmachine-suggested · Relational suggestion, not evidence.