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RGCCA

Regularized and Sparse Generalized Canonical Correlation Analysis for Multiblock 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: 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.

Versions across snapshots

VersionRepositoryFileSize
3.0.3 rolling linux/jammy R-4.5 RGCCA_3.0.3.tar.gz 609.3 KiB
3.0.3 rolling linux/noble R-4.5 RGCCA_3.0.3.tar.gz 608.9 KiB
3.0.3 rolling source/ R- RGCCA_3.0.3.tar.gz 469.8 KiB
3.0.3 latest linux/jammy R-4.5 RGCCA_3.0.3.tar.gz 609.3 KiB
3.0.3 latest linux/noble R-4.5 RGCCA_3.0.3.tar.gz 608.9 KiB
3.0.3 latest source/ R- RGCCA_3.0.3.tar.gz 469.8 KiB
3.0.3 2026-04-26 source/ R- RGCCA_3.0.3.tar.gz 469.8 KiB
3.0.3 2026-04-23 source/ R- RGCCA_3.0.3.tar.gz 469.8 KiB
3.0.3 2026-04-09 windows/windows R-4.5 RGCCA_3.0.3.zip 609.9 KiB
3.0.3 2025-04-20 source/ R- RGCCA_3.0.3.tar.gz 469.8 KiB

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