CRAN/E | RGCCA

RGCCA

Regularized and Sparse Generalized Canonical Correlation Analysis for Multiblock Data

Installation

About

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: to study the relationships between blocks and to identify subsets of variables of each block which are active in their relationships with the other blocks. This package allows to (i) run R/SGCCA and related methods, (ii) help the user to find out the optimal parameters for R/SGCCA such as regularization parameters (tau or sparsity), (iii) evaluate the stability of the RGCCA results and their significance, (iv) build predictive models from the R/SGCCA. (v) Generic print() and plot() functions apply to all these functionalities.

Citation RGCCA citation info
github.com/rgcca-factory/RGCCA
rgcca-factory.github.io/RGCCA/
Bug report File report

Key Metrics

Version 3.0.3
R ≥ 3.5
Published 2023-12-11 141 days ago
Needs compilation? no
License GPL-3
CRAN checks RGCCA results

Downloads

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Maintainer

Maintainer

Arthur Tenenhaus

arthur.tenenhaus@centralesupelec.fr

Authors

Fabien Girka

aut

Etienne Camenen

aut

Caroline Peltier

aut

Arnaud Gloaguen

aut

Vincent Guillemot

aut

Laurent Le Brusquet

ths

Arthur Tenenhaus

aut / ths / cre

Material

README
NEWS
Reference manual
Package source

Vignettes

RGCCA

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

RGCCA archive

Depends

R ≥ 3.5

Imports

caret
Deriv
ggplot2 ≥ 3.4.0
ggrepel
graphics
gridExtra
MASS
matrixStats
methods
parallel
pbapply
rlang
stats

Suggests

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