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Cited by 377

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CCA: An R Package to Extend Canonical Correlation Analysis

Open access
Gonzalez, Ignacio, Déjean, Sébastien, Martin, Pascal, Baccini, Alain·2008·Journal of Statistical Software

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, http://CRAN.R-project.org/), 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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Metadata

Authors
Gonzalez, I., Déjean, S., Martin, P., & Baccini, A.
Venue
Journal of Statistical Software
Published
2008
Volume
23
Issue
12
ISSN
1548-7660 (ISSN-L)
OpenAlex
W1880944740
Cited by
377
References
9
FWCI
19.61
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: CCA: An R Package to Extend Canonical Correlation Analysis. https://app.cochat.ai/papers/10.18637/jss.v023.i12
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Gonzalez, I., Déjean, S., Martin, P., & Baccini, A. (2008). CCA: An R Package to Extend Canonical Correlation Analysis. Journal of Statistical Software. https://doi.org/10.18637/jss.v023.i12

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.