Koren.16S               16S microbiome atherosclerosis study
auroc                   Area Under the Curve (AUC) and Receiver
                        Operating Characteristic (ROC) curves for
                        supervised classification
background.predict      Calculate prediction areas
block.pls               N-integration with Projection to Latent
                        Structures models (PLS)
block.plsda             N-integration with Projection to Latent
                        Structures models (PLS) with Discriminant
                        Analysis
block.spls              N-integration and feature selection with sparse
                        Projection to Latent Structures models (sPLS)
block.splsda            N-integration and feature selection with
                        Projection to Latent Structures models (PLS)
                        with sparse Discriminant Analysis
breast.TCGA             Breast Cancer multi omics data from TCGA
breast.tumors           Human Breast Tumors Data
cim                     Clustered Image Maps (CIMs) ("heat maps")
cimDiablo               Clustered Image Maps (CIMs) ("heat maps") for
                        DIABLO
circosPlot              circosPlot for DIABLO
color.jet               Color Palette for mixOmics
diverse.16S             16S microbiome data: most diverse bodysites
                        from HMP
estim.regul             Estimate the parameters of regularization for
                        Regularized CCA
explained_variance      Calculation of explained variance
get.confusion_matrix    Create confusion table and calculate the
                        Balanced Error Rate
image.estim.regul       Plot the cross-validation score.
image.tune.rcc          Plot the cross-validation score.
imgCor                  Image Maps of Correlation Matrices between two
                        Data Sets
ipca                    Independent Principal Component Analysis
linnerud                Linnerud Dataset
liver.toxicity          Liver Toxicity Data
logratio.transfo        Log-ratio transformation
map                     Classification given Probabilities
mat.rank                Matrix Rank
mint.block.pls          NP-integration
mint.block.plsda        NP-integration with Discriminant Analysis
mint.block.spls         NP-integration for integration with variable
                        selection
mint.block.splsda       NP-integration with Discriminant Analysis and
                        variable selection
mint.pca                P-integration with Principal Component Analysis
mint.pls                P-integration
mint.plsda              P-integration with Projection to Latent
                        Structures models (PLS) with Discriminant
                        Analysis
mint.spls               P-integration with variable selection
mint.splsda             P-integration with Discriminant Analysis and
                        variable selection
mixOmics                PLS-derived methods: one function to rule them
                        all!
multidrug               Multidrug Resistence Data
nearZeroVar             Identification of zero- or near-zero variance
                        predictors
network                 Relevance Network for (r)CCA and (s)PLS
                        regression
nipals                  Non-linear Iterative Partial Least Squares
                        (NIPALS) algorithm
nutrimouse              Nutrimouse Dataset
pca                     Principal Components Analysis
pcatune                 Tune the number of principal components in PCA
perf                    Compute evaluation criteria for PLS, sPLS,
                        PLS-DA, sPLS-DA, MINT and DIABLO
plot.perf               Plot for model performance
plot.rcc                Canonical Correlations Plot
plot.tune               Plot for model performance
plotArrow               Arrow sample plot
plotDiablo              Graphical output for the DIABLO framework
plotIndiv               Plot of Individuals (Experimental Units)
plotLoadings            Plot of Loading vectors
plotVar                 Plot of Variables
pls                     Partial Least Squares (PLS) Regression
plsda                   Partial Least Squares Discriminant Analysis
                        (PLS-DA).
predict.pls             Predict Method for (mint).(block).(s)pls(da)
                        methods
print                   Print Methods for CCA, (s)PLS, PCA and Summary
                        objects
rcc                     Regularized Canonical Correlation Analysis
selectVar               Output of selected variables
sipca                   Independent Principal Component Analysis
spca                    Sparse Principal Components Analysis
spls                    Sparse Partial Least Squares (sPLS)
splsda                  Sparse Partial Least Squares Discriminant
                        Analysis (sPLS-DA)
srbct                   Small version of the small round blue cell
                        tumors of childhood data
stemcells               Human Stem Cells Data
study_split             divides a data matrix in a list of matrices
                        defined by a factor
summary                 Summary Methods for CCA and PLS objects
tune                    Generic function to choose the parameters in
                        the different methods in mixOmics
tune.block.splsda       Tuning function for block.splsda method
                        (N-integration with sparse Discriminant
                        Analysis)
tune.mint.splsda        Estimate the parameters of mint.splsda method
tune.pca                Tune the number of principal components in PCA
tune.rcc                Estimate the parameters of regularization for
                        Regularized CCA
tune.spls               Tuning functions for sPLS method
tune.splsda             Tuning functions for sPLS-DA method
tune.splslevel          Tuning functions for multilevel sPLS method
unmap                   Dummy matrix for an outcome factor
vac18                   Vaccine study Data
vac18.simulated         Simulated data based on the vac18 study for
                        multilevel analysis
vip                     Variable Importance in the Projection (VIP)
withinVariation         Within matrix decomposition for repeated
                        measurements (cross-over design)
wrapper.rgcca           mixOmics wrapper for Regularised Generalised
                        Canonical Correlation Analysis (rgcca)
wrapper.sgcca           mixOmics wrapper for Sparse Generalised
                        Canonical Correlation Analysis (sgcca)
yeast                   Yeast metabolomic study
