Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Ignacio González, Sébastien Déjean, Pascal G. P. Martin, Alain Baccini
Title: CCA: An R Package to Extend Canonical Correlation Analysis
Abstract: Canonical correlations analysis (CCA) is an exploratory statistical method to highlight correlations between two data sets acquired on the same experimental units. The cancor() function in R (R Development Core Team 2007) performs the core of computations but further work was required to provide the user with additional tools to facilitate the interpretation of the results. We implemented an R package, CCA, freely available from the Comprehensive R Archive Network (CRAN,, to develop numerical and graphical outputs and to enable the user to handle missing values. The CCA package also includes a regularized version of CCA to deal with data sets with more variables than units. Illustrations are given through the analysis of a data set coming from a nutrigenomic study in the mouse.

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Paper: CCA: An R Package to Extend Canonical Correlation Analysis     Download PDF (Downloads: 61473)
CCA_1.1.tar.gz: R source package Download (Downloads: 1650; 18KB)
v23i12.R: R example code from the paper Download (Downloads: 2134; 946B)

DOI: 10.18637/jss.v023.i12

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.