| OmicsPLS-package | Data integration with O2PLS: Two-Way Orthogonal Partial Least Squares |
| adjR2 | Gridwise adjusted R2 for O2PLS |
| crossval_o2m | Cross-validate procedure for O2PLS |
| crossval_o2m_adjR2 | Adjusted Cross-validate procedure for O2PLS |
| loadings | Extract the loadings from an O2PLS fit |
| loadings.o2m | Extract the loadings from an O2PLS fit |
| loocv | K fold CV for O2PLS |
| loocv_combi | K-fold CV based on symmetrized prediction error |
| mse | Calculate mean squared difference |
| o2m | Perform O2-PLS data integration with two-way orthogonal corrections |
| OmicsPLS | Data integration with O2PLS: Two-Way Orthogonal Partial Least Squares |
| orth | Orthogonalize a matrix |
| plot.o2m | Plot one or two loading vectors for class o2m |
| predict.o2m | Predicts X or Y |
| print.cvo2m | Cross-validate procedure for O2PLS |
| print.o2m | Print function for O2PLS. |
| rmsep | Root MSE of Prediction |
| rmsep_combi | Symmetrized root MSE of Prediction |
| scores | Extract the scores from an O2PLS fit |
| scores.o2m | Extract the scores from an O2PLS fit |
| ssq | Calculate Sum of Squares |
| summary.o2m | Summary of an O2PLS fit |
| vnorm | Norm of a vector or columns of a matrix |