| 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 |