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Redundancy Analysis

Redundancy Analysis (RDA) is a multivariate technique developed by van den Wollenberg (1977) that combines multiple regression and principal component analysis. RDA finds linear combinations of predictor variables that best predict variation in response variables, making it ideal for understanding how sets of predictors collectively explain multivariate outcomes.

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Redundancy Analysis

Rekod kaedah taksonomik · latent-structure / psychometrics

van den Wollenberg, A. L. (1977). Redundancy analysis: An alternative for canonical correlation analysis. Psychometrika, 42(2), 207-219. · DOI 10.1007/BF02294050
Legendre, P., & Legendre, L. (1998). Numerical Ecology (2nd ed.). Elsevier. · ISBN 9780444892546
Knudsen, S., Andersen, T., & Hansen, J. (2007). Redundancy analysis of multivariate data using PLS. Chemometrics and Intelligent Laboratory Systems, 87(2), 264-272. · URL

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