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.
- Version3.0.3
- R version≥ 3.5
- LicenseGPL-3
- Needs compilation?No
- RGCCA citation info
- Last release12/11/2023
Documentation
Team
Arthur Tenenhaus
Etienne Camenen
Show author detailsRolesAuthorFabien Girka
Show author detailsRolesAuthorCaroline Peltier
Show author detailsRolesAuthorArnaud Gloaguen
Show author detailsRolesAuthorVincent Guillemot
Show author detailsRolesAuthorLaurent Le Brusquet
Show author detailsRolesThesis advisor
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- Imports9 packages
- Suggests8 packages
- Reverse Suggests2 packages