bin.color |
Internal Functions in mixOmics |
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 |
jet.colors |
Jet Colors Palette |
linnerud |
Linnerud Dataset |
liver.toxicity |
Liver Toxicity Data |
loo |
Internal Functions in mixOmics |
map |
Converts an indicator matrix to class vector |
mat.rank |
Matrix Rank |
Mfold |
Internal Functions in mixOmics |
multidrug |
Multidrug Resistence Data |
nearZeroVar |
Identification of zero- or near-zero variance predictors |
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 |
pcasvd |
Internal Functions in mixOmics |
pcatune |
Tune the number of principal components in PCA |
plot.rcc |
Canonical Correlations Plot |
plot.valid |
Validation 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.spca |
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.pca |
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.pca |
Plot of Variables |
plotVar.pls |
Plot of Variables |
plotVar.plsda |
Plot of Variables |
plotVar.rcc |
Plot of Variables |
plotVar.spca |
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 |
spca |
Sparse Principal Components Analysis |
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) |