BiPlot                  Generates a biplot from the output of an
                        'mvdareg' and 'mvdapca' object
College                 Data for College Level Examination Program and
                        the College Qualification Test
MVComp                  Traditional Multivariate Mean Vector Comparison
MVcis                   Calculate Hotelling's T2 Confidence Intervals
MultCapability          Principal Component Based Multivariate Process
                        Capability Indices
PE                      Percent Explained Variation of X
Penta                   Penta data set
R2s                     Cross-validated R2, R2 for X, and R2 for Y for
                        PLS models
ScoreContrib            Generates a score contribution plot
SeqimputeEM             Sequential Expectation Maximization (EM) for
                        imputation of missing values.
T2                      Generates a Hotelling's T2 Graph
Wang_Chen               Bivariate process data.
Wang_Chen_Sim           Simulated process data from a plastics
                        manufacturer.
Xresids                 Generates a Graph of the X-residuals
XresidualContrib        Generates the squared prediction error
                        contributions and contribution plot
acfplot                 Plot of Auto-correlation Funcion
ap.plot                 Actual versus Predicted Plot and Residuals
                        versus Predicted
bca.cis                 Bias-corrected and Accelerated Confidence
                        Intervals
bidiagpls.fit           Bidiag2 PLS
boot.plots              Plots of the Output of a Bootstrap Simulation
                        for an 'mvdareg' Object
coef.mvdareg            Extract Information From a plsFit Model
coefficients.boots      BCa Summaries for the coefficient of an mvdareg
                        object
coefficients.mvdareg    Extract Summary Information Pertaining to the
                        Coefficients resulting from a PLS model
coefficientsplot2D      2-Dimensionsl Graphical Summary Information
                        Pertaining to the Coefficients of a PLS
coefsplot               Graphical Summary Information Pertaining to the
                        Regression Coefficients
contr.niets             Cell Means Contrast Matrix
ellipse.mvdalab         Ellipses, Data Ellipses, and Confidence
                        Ellipses
imputeBasic             Naive imputation of missing values.
imputeEM                Expectation Maximization (EM) for imputation of
                        missing values.
imputeQs                Quartile Naive Imputation of Missing Values
imputeRough             Naive Imputation of Missing Values for Dummy
                        Variable Model Matrix
introNAs                Introduce NA's into a Dataframe
jk.after.boot           Jackknife After Bootstrap
loadings.boots          BCa Summaries for the loadings of an mvdareg
                        object
loadings.mvdareg        Summary Information Pertaining to the
                        Bootstrapped Loadings
loadingsplot            Graphical Summary Information Pertaining to the
                        Loadings
loadingsplot2D          2-Dimensionsl Graphical Summary Information
                        Pertaining to the Loadings of a PLS or PCA
                        Analysis
mewma                   Generates a Hotelling's T2 Graph of the
                        Multivariate Exponentially Weighted Average
model.matrix.mvdareg    'model.matrix' creates a design (or model)
                        matrix.
mvdaboot                Bootstrapping routine for 'mvdareg' objects
mvdalab-package         Multivariate Data Analysis Laboratory (mvdalab)
mvdaloo                 Leave-one-out routine for 'mvdareg' objects
mvrnorm.svd             Simulate from a Multivariate Normal, Poisson,
                        Exponential, or Skewed Distribution
my.dummy.df             Create a Design Matrix with the Desired
                        Constrasts
no.intercept            Delete Intercept from Model Matrix
pca.nipals              PCA with the NIPALS algorithm
pcaFit                  Principal Component Analysis
perc.cis                Percentile Bootstrap Confidence Intervals
plot.R2s                Plot of R2
plot.cp                 Plotting Function for Score Contributions.
plot.mvcomp             Plot of Multivariate Mean Vector Comparison
plot.mvdareg            General plotting function for 'mvdareg' and
                        'mvdapaca' objects.
plot.plusminus          2D Graph of the PCA scores associated with a
                        plusminusFit
plot.smc                Plotting function for Significant Multivariate
                        Correlation
plot.sr                 Plotting function for Selectivity Ratio.
plot.wrtpls             Plots of the Output of a Permutation
                        Distribution for an 'mvdareg' Object with
                        'method = "bidiagpls"'
plsFit                  Partial Least Squares Regression
plusMinusDat            plusMinusDat data set
plusminus.fit           PlusMinus (Mas-o-Menos)
plusminus.loo           Leave-one-out routine for 'plusminus' objects
plusminusFit            Plus-Minus (Mas-o-Menos) Classifier
predict.mvdareg         Model Predictions From a plsFit Model
print.mvdareg           Print Methods for mvdalab Objects
print.plusminus         Print Methods for plusminus Objects
proCrustes              Comparison of n-point Configurations vis
                        Procrustes Analysis
scoresplot              2D Graph of the scores
smc                     Significant Multivariate Correlation
smc.acfTest             Test of the Residual Significant Multivariate
                        Correlation Matrix for the presence of
                        Autocorrelation
sr                      Selectivity Ratio
weight.boots            BCa Summaries for the weights of an mvdareg
                        object
weights.mvdareg         Extract Summary Information Pertaining to the
                        Bootstrapped weights
weightsplot             Extract Graphical Summary Information
                        Pertaining to the Weights
weightsplot2D           Extract a 2-Dimensional Graphical Summary
                        Information Pertaining to the weights of a PLS
                        Analysis
wrtpls.fit              Weight Randomization Test PLS
y.loadings              Extract Summary Information Pertaining to the
                        y-loadings
y.loadings.boots        Extract Summary Information Pertaining to the
                        y-loadings
