| bin.color |
Regularized CCA Internal Functions |
| breast.tumors |
Human Breast Tumors Data |
| cim |
Clustered Image Maps (CIMs) ("heat maps") |
| cim.default |
Clustered Image Maps (CIMs) ("heat maps") |
| cim.rcc |
Clustered Image Maps (CIMs) ("heat maps") |
| cim.spls |
Clustered Image Maps (CIMs) ("heat maps") |
| estim.regul |
Estimate the parameters of regularization for Regularized CCA |
| estim.regul.default |
Estimate the parameters of regularization for Regularized CCA |
| image.estim.regul |
Plot the cross-validation score. |
| imgCor |
Image Maps of Correlation Matrices between two Data Sets |
| imgCor.default |
Image Maps of Correlation Matrices between two Data Sets |
| jet.colors |
Jet Colors Palette |
| linnerud |
Linnerud Dataset |
| liver.toxicity |
Liver Toxicity Data |
| loo |
Regularized CCA Internal Functions |
| map |
Converts an indicator matrix to class vector |
| mat.rank |
Matrix Rank |
| Mfold |
Regularized CCA Internal Functions |
| multidrug |
Multidrug Resistence Data |
| network |
Relevance Network for (Regularized) CCA and (sparse) PLS regression |
| network.default |
Relevance Network for (Regularized) CCA and (sparse) PLS regression |
| network.rcc |
Relevance Network for (Regularized) CCA and (sparse) PLS regression |
| network.spls |
Relevance Network for (Regularized) CCA and (sparse) PLS regression |
| nipals |
Non-linear Iterative Partial Least Squares (NIPALS) algorithm |
| nutrimouse |
Nutrimouse Dataset |
| pca |
Principal Components Analysis |
| plot.rcc |
Canonical Correlations Plot |
| plot3dIndiv |
Plot of Individuals (Experimental Units) in three dimensions |
| plot3dIndiv.pca |
Plot of Individuals (Experimental Units) in three dimensions |
| plot3dIndiv.pls |
Plot of Individuals (Experimental Units) in three dimensions |
| plot3dIndiv.plsda |
Plot of Individuals (Experimental Units) in three dimensions |
| plot3dIndiv.rcc |
Plot of Individuals (Experimental Units) in three dimensions |
| plot3dIndiv.spls |
Plot of Individuals (Experimental Units) in three dimensions |
| plot3dIndiv.splsda |
Plot of Individuals (Experimental Units) in three dimensions |
| plot3dVar |
Plot of Variables in three dimensions |
| plot3dVar.pca |
Plot of Variables in three dimensions |
| plot3dVar.pls |
Plot of Variables in three dimensions |
| plot3dVar.plsda |
Plot of Variables in three dimensions |
| plot3dVar.rcc |
Plot of Variables in three dimensions |
| plot3dVar.spls |
Plot of Variables in three dimensions |
| plot3dVar.splsda |
Plot of Variables in three dimensions |
| plotIndiv |
Plot of Individuals (Experimental Units) |
| plotIndiv.pls |
Plot of Individuals (Experimental Units) |
| plotIndiv.plsda |
Plot of Individuals (Experimental Units) |
| plotIndiv.rcc |
Plot of Individuals (Experimental Units) |
| plotIndiv.spls |
Plot of Individuals (Experimental Units) |
| plotIndiv.splsda |
Plot of Individuals (Experimental Units) |
| plotVar |
Plot of Variables |
| plotVar.pls |
Plot of Variables |
| plotVar.plsda |
Plot of Variables |
| plotVar.rcc |
Plot of Variables |
| plotVar.spls |
Plot of Variables |
| plotVar.splsda |
Plot of Variables |
| pls |
Partial Least Squares (PLS) Regression |
| plsda |
Partial Least Squares Discriminate Analysis (PLS-DA). |
| predict.pls |
Predict Method for PLS, sparse PLS, PLSDA Regression or Sparse PLSDA |
| predict.plsda |
Predict Method for PLS, sparse PLS, PLSDA Regression or Sparse PLSDA |
| predict.spls |
Predict Method for PLS, sparse PLS, PLSDA Regression or Sparse PLSDA |
| predict.splsda |
Predict Method for PLS, sparse PLS, PLSDA Regression or Sparse PLSDA |
| print |
Print Methods for CCA, (s)PLS and Summary objects |
| print.pls |
Print Methods for CCA, (s)PLS and Summary objects |
| print.rcc |
Print Methods for CCA, (s)PLS and Summary objects |
| print.spls |
Print Methods for CCA, (s)PLS and Summary objects |
| print.summary |
Print Methods for CCA, (s)PLS and Summary objects |
| rcc |
Regularized Canonical Correlation Analysis |
| rcc.default |
Regularized Canonical Correlation Analysis |
| s.match |
Plot of Paired Coordinates |
| scatterutil.base |
Graphical utility functions from ade4 |
| scatterutil.eti |
Graphical utility functions from ade4 |
| scatterutil.grid |
Graphical utility functions from ade4 |
| spls |
Sparse Partial Least Squares (sPLS) |
| splsda |
Sparse Partial Least Squares Discriminate Analysis (sPLS-DA) |
| srbct |
Small version of the small round blue cell tumors of childhood data |
| summary |
Summary Methods for CCA and PLS objects |
| summary.pls |
Summary Methods for CCA and PLS objects |
| summary.rcc |
Summary Methods for CCA and PLS objects |
| summary.spls |
Summary Methods for CCA and PLS objects |
| unmap |
Converts a class vector to an indicator matrix |
| valid |
Compute validation criterion for PLS and Sparse PLS |
| vip |
Variable Importance in the Projection (VIP) |