| biplotPLS | PLS biplot | 
| checkinput | Check input | 
| confusionMatrix | Confusion matrix | 
| crispEM | Effect matrix for the crisp multilevel tutorial | 
| customParams | Make custom parameters for internal modelling | 
| getBER | Get BER | 
| getMISS | Get number of misclassifications | 
| getVar | Get min, mid or max model from Elastic Net modelling | 
| getVIRank | Get variable importance | 
| get_rmsep | Get RMSEP | 
| H0_reference | Get reference distribution for resampling tests | 
| H0_test | Perform permutation or resampling tests | 
| IDR | Subject identifiers for the rye metabolomics regression tutorial | 
| IDR2 | Subject identifiers for the rye metabolomics regression tutorial, using unique individuals | 
| mergeModels | Merge two MUVR class objects | 
| MUVR2 | MUVR2 with PLS and RF | 
| MUVR2_EN | MUVR2 with EN | 
| nearZeroVar | Identify variables with near zero variance | 
| onehotencoding | One hot encoding | 
| permutationPlot | Plot permutation analysis | 
| plotMV | Plot predictions | 
| plotPCA | PCA score plot | 
| plotPerm | Plot for comparison of actual model fitness vs permutation/resampling | 
| plotPred | Plot predictions for PLS regression | 
| plotStability | Plot stability | 
| plotVAL | Plot validation metric | 
| plotVIRank | Plot variable importance ranking | 
| pPerm | Calculate permutation p-value Calculate perutation p-value of actual model performance vs null hypothesis distribution. 'pPerm' will calculate the cumulative (1-tailed) probability of 'actual' belonging to 'permutation_distribution'. 'side' is guessed by actual value compared to median(permutation_distribution). Test is performed on original data OR ranked for non-parametric statistics. | 
| predMV | Predict outcomes Predict MV object using a MUVR class object and a X testing set. At present, this function only supports predictions for PLS regression type problems. | 
| preProcess | Perform matrix pre-processing | 
| Q2_calculation | Q2 calculation | 
| qMUVR2 | Wrapper for speedy access to MUVR2 (autosetup of parallelization) | 
| rdCV | Wrapper for repeated double cross-validation without variable selection | 
| rdcvNetParams | Make custom parameters for rdcvNet internal modelling | 
| sampling_from_distribution | Sampling from the distribution of something | 
| varClass | Report variables belonging to different classes | 
| Xotu | Microbiota composition in mosquitos for the classification tutorial | 
| XRVIP | Metabolomics data for the rye metabolomics regression tutorial | 
| XRVIP2 | Metabolomics data for the rye metabolomics regression tutorial, using unique individuals | 
| Yotu | Village of capture of mosquitos for the classification tutorial | 
| YR | Rye consumption for the rye metabolomics regression tutorial | 
| YR2 | Rye consumption for the rye metabolomics regression tutorial, using unique individuals |