| RSCA-package | RSCA: A package for regularized simultaneous component analysis (SCA) for data integration. |
| cv_sparseSCA | A K-fold cross-validation procedure when common/distinctive processes are unknown with Lasso and Group Lasso penalties. |
| cv_structuredSCA | A K-fold cross-validation procedure when common/distinctive processes are known, with a Lasso penalty. |
| DISCOsca | DISCO-SCA rotation. |
| Herring | Herring data |
| maxLGlasso | An algorithm for determining the smallest values for Lasso and Group Lasso tuning parameters that yield all zeros. |
| pca_gca | PCA-GCA method for selecting the number of common and distinctive components. |
| plot.CVsparseSCA | Ploting Cross-validation results |
| plot.CVstructuredSCA | Cross-validation plot |
| pre_process | Standardize the given data matrix per column, over the rows, with multiple imputation for missing data. |
| RSCA | RSCA: A package for regularized simultaneous component analysis (SCA) for data integration. |
| sparseSCA | Variable selection with Lasso and Group Lasso with a multi-start procedure. |
| structuredSCA | Variable selection algorithm with a predefined component loading structure. |
| summary.CVsparseSCA | Display a summary of the results of 'cv_sparseSCA()'. |
| summary.CVstructuredSCA | Display a summary of the results of 'cv_structuredSCA()'. |
| summary.DISCOsca | Display a summary of the results of 'DISCOsca()'. |
| summary.sparseSCA | Display a summary of the results of 'sparseSCA()'. |
| summary.structuredSCA | Display a summary of the results of 'structuredSCA()'. |
| summary.undoS | Display a summary of the results of 'undoShrinkage()'. |
| summary.VAF | Display a summary of the results of 'VAF()'. |
| TuckerCoef | Tucker coefficient of congruence. |
| undoShrinkage | Undo shrinkage. |
| VAF | Proportion of variance accounted for (VAF) for each block and each principal component. |