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RGCCA
View on CRAN: Click
here
Download and install RGCCA package within the R console
Install from CRAN:
install.packages("RGCCA")
Install from Github:
library("remotes")
install_github("cran/RGCCA")
Install by package version:
library("remotes")
install_version("RGCCA", "3.0.3")
Attach the package and use:
library("RGCCA")
Maintained by
Arthur Tenenhaus
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-10-29
Latest Update: 2023-12-11
Description:
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.
How to cite:
Arthur Tenenhaus (2012). RGCCA: Regularized and Sparse Generalized Canonical Correlation Analysis for Multiblock Data. R package version 3.0.3, https://cran.r-project.org/web/packages/RGCCA
Previous versions and publish date:
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Other R packages that RGCCA depends,
imports, suggests or enhances
Functions, R codes and Examples using
the RGCCA R package
Some associated functions: BinarySearch . Russett . cov2 . defl.select . miscrossprod . rgcca . rgccak . scale2 . sgcca . sgccak . soft . soft.threshold . tau.estimate .
Some associated R codes: BinarySearch.R . cov2.R . defl.select.R . deflation.R . initsvd.R . miscrossprod.R . norm2.R . rgcca.R . rgccak.R . scale2.R . sgcca.R . sgccak.R . soft.R . soft.threshold.R . tau.estimate.R . Full RGCCA package functions and examples
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