| aggmean | Centers of classes |
| aicplsr | AIC and Cp for Univariate PLSR Models |
| asdgap | asdgap |
| blocks | Block autoscaling |
| cassav | cassav |
| cglsr | CG Least Squares Models |
| checkdupl | Duplicated rows in datasets |
| checkna | Find and count NA values in a dataset |
| covsel | CovSel |
| dderiv | Derivation by finite difference |
| detrend | Polynomial de-trend transformation |
| dfplsr_cg | Degrees of freedom of Univariate PLSR Models |
| dkplsr | Direct KPLSR Models |
| dkrr | Direct KRR Models |
| dmnorm | Multivariate normal probability density |
| dtagg | Summary statistics of data subsets |
| dummy | Table of dummy variables |
| epo | External parameter orthogonalization (EPO) |
| euclsq | Matrix of distances |
| fda | Factorial discriminant analysis |
| forages | forages |
| getknn | KNN selection |
| gram | Kernel functions |
| gridcv | Cross-validation |
| gridscore | Tuning of predictive models on a validation dataset |
| headm | Display of the first part of a data set |
| interpl | Resampling of spectra by interpolation methods |
| knnda | KNN-DA |
| knnr | KNN-R |
| kpca | KPCA |
| kplsr | KPLSR Models |
| kplsrda | KPLSR-DA models |
| krr | KRR (LS-SVMR) |
| krrda | KRR-DA models |
| lda | LDA and QDA |
| lmr | Linear regression models |
| lmrda | LMR-DA models |
| locw | Locally weighted models |
| lwplsda_agg | Aggregation of KNN-LWPLSDA models with different numbers of... |
| lwplsr | KNN-LWPLSR |
| lwplsr_agg | Aggregation of KNN-LWPLSR models with different numbers of... |
| lwplsrda | KNN-LWPLS-DA Models |
| matW | Between and within covariance matrices |
| mavg | Smoothing by moving average |
| mbplsda | multi-block PLSDA models |
| mbplsr | multi-block PLSR algorithms |
| mbplsr_mbplsda_allsteps | MBPLSR or MBPLSDA analysis steps |
| octane | octane |
| odis | Orthogonal distances from a PCA or PLS score space |
| orthog | Orthogonalization of a matrix to another matrix |
| ozone | ozone |
| pca | PCA algorithms |
| pinv | Moore-Penrose pseudo-inverse of a matrix |
| plotjit | Jittered plot |
| plotscore | Plotting errors rates |
| plotsp | Plotting spectra |
| plotxna | Plotting Missing Data in a Matrix |
| plotxy | 2-d scatter plot |
| plsda | PLSDA models |
| plsda_agg | PLSDA with aggregation of latent variables |
| plsr | PLSR algorithms |
| plsr_agg | PLSR with aggregation of latent variables |
| plsr_plsda_allsteps | PLSR or PLSDA analysis steps |
| rmgap | Removing vertical gaps in spectra |
| rr | Linear Ridge Regression |
| rrda | RR-DA models |
| sampcla | Within-class sampling |
| sampdp | Duplex sampling |
| sampks | Kennard-Stone sampling |
| savgol | Savitzky-Golay smoothing |
| scordis | Score distances (SD) in a PCA or PLS score space |
| scores | Residuals and prediction error rates |
| segmkf | Segments for cross-validation |
| selwold | Heuristic selection of the dimension of a latent variable... |
| snv | Standard normal variate transformation (SNV) |
| soplsda | Block dimension reduction by SO-PLS-DA |
| soplsr | Block dimension reduction by SO-PLS |
| soplsr_soplsda_allsteps | SOPLSR or SOPLSDA analysis steps |
| sourcedir | Source R functions in a directory |
| summ | Description of the quantitative variables of a data set |
| svm | SVM Regression and Discrimination |
| transform | Generic transform function |
| vip | Variable Importance in Projection (VIP) |
| wdist | Distance-based weights |
| xfit | Matrix fitting from a PCA or PLS model |
