Introduction | The RGCCA framework | Formulation | Sample-based RGCCA | Special cases | Sparse generalized canonical correlation analysis | A master algorithm for the RGCCA framework | The specific case of RGCCA | The specific case of SGCCA | Higher level RGCCA algorithm | Average variance explained | The RGCCA package | Software design | Case study: the Russett dataset | High dimensional case study: the glioma study | Conclusion | Acknowledgments | References
Package: RGCCA 3.0.3
Arthur Tenenhaus
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.
Authors:
RGCCA_3.0.3.tar.gz
RGCCA_3.0.3.zip(r-4.7)RGCCA_3.0.3.zip(r-4.6)RGCCA_3.0.3.zip(r-4.5)
RGCCA_3.0.3.tgz(r-4.6-any)RGCCA_3.0.3.tgz(r-4.5-any)
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RGCCA_3.0.3.tgz(r-4.6-emscripten)
|manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RGCCA/json (API)
| # Install 'RGCCA' in R: |
| install.packages('RGCCA', repos = c('https://rgcca-factory.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rgcca-factory/rgcca/issues
Pkgdown/docs site:https://rgcca-factory.github.io
Last updated from:85238a2dce. Checks:8 OK, 1 ERROR. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 239 | ||
| source / vignettes | ERROR | 286 | ||
| linux-release-x86_64 | OK | 244 | ||
| macos-release-arm64 | OK | 262 | ||
| macos-oldrel-arm64 | OK | 177 | ||
| windows-devel | OK | 201 | ||
| windows-release | OK | 183 | ||
| windows-oldrel | OK | 194 | ||
| wasm-release | OK | 151 |
Exports:available_methodsrgccargcca_bootstraprgcca_cvrgcca_permutationrgcca_predictrgcca_stabilityrgcca_transform
Dependencies:abindcaretclasscliclockcodetoolscpp11data.tableDerivdiagramdigestdplyre1071farverforeachfuturefuture.applygenericsggplot2ggrepelglobalsgluegowergridExtragtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmatrixStatsModelMetricsnlmennetnumDerivparallellypbapplypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrpartS7scalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr
Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.
Multiblock data analysis with the RGCCA package
Last update: 2023-10-05
Started: 2023-04-12
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Available methods for RGCCA | available_methods |
| European Customer Satisfaction Index | ECSI |
| Plot a fitted object from the RGCCA package | plot.rgcca plot.rgcca_bootstrap plot.rgcca_cv plot.rgcca_permutation plot.rgcca_stability |
| Print a fitted object from the RGCCA package | print.rgcca print.rgcca_bootstrap print.rgcca_cv print.rgcca_permutation print.rgcca_stability |
| Regularized Generalized Canonical Correlation Analysis (RGCCA) | rgcca |
| Bootstrap confidence intervals and p-values | rgcca_bootstrap |
| Tune RGCCA parameters by cross-validation | rgcca_cv |
| Tune the S/RGCCA hyper-parameters by permutation | rgcca_permutation |
| Make predictions using RGCCA | rgcca_predict |
| Identify the most stable variables with SGCCA | rgcca_stability |
| Reduce dimensionality using RGCCA | rgcca_transform |
| Russett data | Russett |
| Summary of a fitted object from the RGCCA package | summary.rgcca summary.rgcca_bootstrap summary.rgcca_cv summary.rgcca_permutation summary.rgcca_stability |
