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.
Version: 3.0.3 Depends: R (≥ 3.5) Imports: caret, Deriv, ggplot2 (≥ 3.4.0), ggrepel, graphics, gridExtra, MASS, matrixStats, methods, parallel, pbapply, rlang, stats Suggests: devtools, FactoMineR, knitr, pander, rmarkdown, rticles, testthat, vdiffr Published: 2023-12-11 DOI: 10.32614/CRAN.package.RGCCA Author: Fabien Girka [aut], Etienne Camenen [aut], Caroline Peltier [aut], Arnaud Gloaguen [aut], Vincent Guillemot [aut], Laurent Le Brusquet [ths], Arthur Tenenhaus [aut, ths, cre] Maintainer: Arthur Tenenhaus <arthur.tenenhaus at centralesupelec.fr> BugReports: https://github.com/rgcca-factory/RGCCA/issues License: GPL-3 URL: https://github.com/rgcca-factory/RGCCA, https://rgcca-factory.github.io/RGCCA/ NeedsCompilation: no Citation: RGCCA citation info Materials: README NEWS CRAN checks: RGCCA resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4