| aicplsr | AIC and Cp for PLSR1 Models |
| bcoef | b-coefficients for PCR and PLSR models |
| blockpls | Block dimension reduction by PCA or PLS |
| blockscal | Block autoscaling |
| blocksel | Block selection in a matrix |
| blocksopls | Block dimension reduction by SO-PCA or SO-PLS |
| centr | Centers of classes |
| checkdupl | Find and remove duplicated row observations between two data... |
| checkna | Find and count NA values in a data set |
| covsel | CovSel |
| cppca | Mallows's Cp for PCA Models |
| cvfit | Cross-validation of a prediction model |
| cvpca_ia | Cross-validation of a PCA model by Missing Data Imputation |
| dadis | DA using the dissimilarity to class centers |
| daglm | DA using GLIM Regression on the Y-Dummy table |
| dalm | DA using Linear Regression on the Y-Dummy table |
| daprob | Probabilistic DA (LDA and QDA) |
| darr | DA using Ridge or Kernel Ridge Regression on the Y-Dummy... |
| dasdod | DA using a SIMCA index |
| datcass | datcass |
| datforages | datforages |
| datoctane | datoctane |
| datozone | datozone |
| dderiv | Derivation by finite difference |
| detrend | Detrend transformation |
| dfpca_div | Degrees of freedom of PCA Models |
| dfplsr_cov | Degrees of freedom of PLSR1 Models |
| dis | Dissimilarities between row observations of a matrix and a... |
| dmnorm | Probability density prediction |
| dtaggregate | Summary statistics with data subsets |
| dummy | Table of dummy variables |
| fda | Factorial discriminant analysis |
| getknn | kNN selection |
| headm | Return the first part of a matrix or data frame |
| inlr | Blocks for INLR |
| kernels | Kernel |
| kgram | Kernel Gram matrices |
| knnr | KNN Regression and Discrimination |
| kpls | Non Linear Kernel PCA and PLS |
| kplsda | Non linear kernel PCDA and PLSDA models |
| kpls_nipals | Non linear kernel PLS algorithm |
| kplsr | Non linear kernel PCR and PLSR Models |
| krr | Non Linear Kernel Ridge Regression |
| lmr | Multiple Linear Regression Models |
| locw | Locally weighted models |
| lwplsr | KNN-LWPLSR & DA |
| matdis | Dissimilarity matrix (between observations) |
| matW | Between and within covariance matrices |
| mavg | Smoothing by moving average |
| mse | Prediction error rates |
| odis | Orthogonal distances from a PCA or PLS score space |
| orthog | Orthogonalization of a matrix to another matrix |
| outstah | Outlyingness measures |
| pca_rob | Robust PCA algorithms |
| pca_svd | PCA algorithms |
| pinv | Moore-Penrose pseudo-inverse of a matrix |
| plotjt | Jittered plot |
| plotsl | Plot of slopes of between elemnts of a vector |
| plotsp | Plotting spectra |
| plotxna | Plotting Missing Data in a Matrix |
| plotxy | 2-d scatter plot |
| pls | PCA and PLS |
| plsda | PCDA and PLSDA |
| pls_iw | Robust PLS1 algorithm (iterative Re-Weighting) |
| pls_kernel | PLS algorithms |
| plsr | PCR and PLSR Models |
| pls_rob | Robust PLS1 algorithm |
| rr | Linear Ridge Regression |
| sampclas | 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 |
| segmkf | Segments for cross-validation |
| selangle | Heuristic selection of the dimension of a PCA or PLS model... |
| selbroken | Heuristic selection of the dimension of a PCA model with the... |
| selcoll | Heuristic selection of the dimension of a PCA or PLS model... |
| selhorn | Heuristic selection of the dimension of a PCA model with the... |
| selkaiser | Heuristic selection of the dimension of a PCA model with the... |
| selkarlis | Heuristic selection of the dimension of a PCA model with the... |
| selscree | Scree plots for PCA or PLS |
| selsign | Heuristic selection of the dimension of regression models... |
| selwik | Heuristic selection of the dimension of PLSR models with a... |
| selwold | Heuristic selection of the dimension of a latent variable... |
| snv | Standard normal variate transformation (SNV) |
| sourcedir | Source R functions in a directory |
| splitpar | Split a parameter value within an interval |
| stackavg | Stacking for predictions models |
| summ | Summary of the variables of a data set |
| svmr | SVM Regression or Discrimination |
| wdist | Weights for distances |
| xfit | Matrix fitting from scores and loadings matrices and SSR... |
| ximputia | Missing Data Imputation using PCA and the Iterative Algorithm... |
| xinterp | Resampling of spectra by nterpolation methods |
