aggmean                 Centers of classes
aicplsr                 AIC and Cp for Univariate PLSR Models
asdgap                  asdgap
blockscal               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
eposvd                  External parameter orthogonalization (EPO)
euclsq                  Matrix of distances
fda                     Factorial discriminant analysis
forages                 forages
getknn                  KNN selection
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
krbf                    Kernel functions
krr                     KRR (LS-SVMR)
krrda                   KRR-DA models
lda                     LDA and QDA
lmr                     Linear regression models
lmrda                   LMR-DA models
locw                    Locally weighted models
lwplsr                  KNN-LWPLSR
lwplsr_agg              Aggregation of KNN-LWPLSR models with different
                        numbers of LVs
lwplsrda                KNN-LWPLS-DA Models
lwplsrda_agg            Aggregation of KNN-LWPLSDA models with
                        different numbers of LVs
matW                    Between and within covariance matrices
mavg                    Smoothing by moving average
mbplsr                  multi-block PLSR algorithms
mbplsr_mbplsda_allsteps
                        MBPLSR or MBPLSDA analysis steps
mbplsrda                multi-block PLSDA models
mse                     Residuals and prediction error rates
octane                  octane
odis                    Orthogonal distances from a PCA or PLS score
                        space
orthog                  Orthogonalization of a matrix to another matrix
ozone                   ozone
pcasvd                  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
plskern                 PLSR algorithms
plsr_agg                PLSR with aggregation of latent variables
plsr_plsda_allsteps     PLSR or PLSDA analysis steps
plsrda                  PLSDA models
plsrda_agg              PLSDA with aggregation of latent variables
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
segmkf                  Segments for cross-validation
selwold                 Heuristic selection of the dimension of a
                        latent variable model with the Wold's criterion
snv                     Standard normal variate transformation (SNV)
soplsr                  Block dimension reduction by SO-PLS
soplsr_soplsda_allsteps
                        SOPLSR or SOPLSDA analysis steps
soplsrda                Block dimension reduction by SO-PLS-DA
sourcedir               Source R functions in a directory
summ                    Description of the quantitative variables of a
                        data set
svmr                    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
