RGCCA: Regularized and Sparse Generalized Canonical Correlation Analysis for Multiblock Data

Multiblock data analysis concerns the analysis of several sets of variables (blocks) observed on the same group of individuals. The main aims of the RGCCA package are: (i) to study the relationships between blocks and (ii) to identify subsets of variables of each block which are active in their relationships with the other blocks.

Version:	2.1.2
Imports:	MASS, Deriv
Suggests:	knitr, rmarkdown, ggplot2
Published:	2017-05-11
Author:	Arthur Tenenhaus and Vincent Guillemot
Maintainer:	Arthur Tenenhaus <arthur.tenenhaus at centralesupelec.fr>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
CRAN checks:	RGCCA results

Documentation:

Reference manual:	RGCCA.pdf
Vignettes:	The RGCCA package for Regularized/Sparse Generalized Canonical Correlation Analysis

Downloads:

Package source:	RGCCA_2.1.2.tar.gz
Windows binaries:	r-devel: RGCCA_2.1.2.zip, r-release: RGCCA_2.1.2.zip, r-oldrel: RGCCA_2.1.2.zip
macOS binaries:	r-release (arm64): RGCCA_2.1.2.tgz, r-oldrel (arm64): RGCCA_2.1.2.tgz, r-release (x86_64): RGCCA_2.1.2.tgz, r-oldrel (x86_64): RGCCA_2.1.2.tgz
Old sources:	RGCCA archive

Reverse dependencies:

Reverse imports:	multiblock, RegularizedSCA
Reverse suggests:	RVAideMemoire

Linking:

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