RGCCA: Regularized and Sparse Generalized Canonical Correlation Analysis for Multi-Block Data

Multi-block 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
Imports: MASS, methods
Published: 2017-01-22
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

Downloads:

Reference manual: RGCCA.pdf
Package source: RGCCA_2.1.tar.gz
Windows binaries: r-devel: RGCCA_2.1.zip, r-release: RGCCA_2.1.zip, r-oldrel: RGCCA_2.1.zip
OS X El Capitan binaries: r-release: RGCCA_2.1.tgz
OS X Mavericks binaries: r-oldrel: RGCCA_2.1.tgz
Old sources: RGCCA archive

Reverse dependencies:

Reverse imports: cocoreg

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