mvdalab: Multivariate Data Analysis Laboratory

An open-source implementation of latent variable methods and multivariate modeling tools. The focus is on exploratory analyses using dimensionality reduction methods including low dimensional embedding, classical multivariate statistical tools , and tools for enhanced interpretation of machine learning methods (i.e. intelligible models to provide important information for end-users). Target domains include extension to dedicated applications e.g. for manufacturing process modeling, spectroscopic analyses, and data mining.

Install the latest version of this package by entering the following in R:
AuthorNelson Lee Afanador, Thanh Tran, Lionel Blanchet, and Richard Baumgartner
Date of publication2017-03-01 08:36:29
MaintainerNelson Lee Afanador <>

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Man pages

acfplot: Plot of Auto-correlation Funcion

ap.plot: Actual versus Predicted Plot and Residuals versus Predicted

bca.cis: Bias-corrected and Accelerated Confidence Intervals Bidiag2 PLS

BiPlot: Generates a biplot from the output of an 'mvdareg' and...

boot.plots: Plots of the Output of a Bootstrap Simulation for an...

coefficients: Extract Summary Information Pertaining to the Coefficients... BCa Summaries for the coefficient of an mvdareg object

coefficientsplot2D: 2-Dimensionsl Graphical Summary Information Pertaining to the...

coef.mvdareg: Extract Information From a plsFit Model

coefsplot: Graphical Summary Information Pertaining to the Regression...

College: Data for College Level Examination Program and the College...

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...

imputeQs: Quartile Naive Imputation of Missing Values

imputeRough: Naive Imputation of Missing Values for Dummy Variable Model...

introNAs: Introduce NA's into a Dataframe

jk.after.boot: Jackknife After Bootstrap

loadings: Summary Information Pertaining to the Bootstrapped Loadings BCa Summaries for the loadings of an mvdareg object

loadingsplot: Graphical Summary Information Pertaining to the Loadings

loadingsplot2D: 2-Dimensionsl Graphical Summary Information Pertaining to the...

mewma: Generates a Hotelling's T2 Graph of the Multivariate...

model.matrix.mvdalab: 'model.matrix' creates a design (or model) matrix.

MVcis: Calculate Hotelling's T2 Confidence Intervals

MVComp: Traditional Multivariate Mean Vector Comparison

mvdaboot: Bootstrapping routine for 'mvdareg' objects

mvdalab-package-title: Multivariate Data Analysis Laboratory (mvdalab)

mvdaloo: Leave-one-out routine for 'mvdareg' objects

mvrnorm.svd: Simulate from a Multivariate Normal, Poisson, Exponential, or...

my.dummy.df: Create a Design Matrix with the Desired Constrasts

no.intercept: Delete Intercept from Model Matrix

pcaFit: Principal Component Analysis

pca.nipals: PCA with the NIPALS algorithm

PE: Percent Explained Variation of X

Penta: Penta data set

perc.cis: Percentile Bootstrap Confidence Intervals

plot.cp: Plotting Function for Score Contributions.

plot.mvcomp: Plot of Multivariate Mean Vector Comparison

plot.mvdareg: General plotting function for 'mvdareg' and 'mvdapaca'...

plot.plusminus: 2D Graph of the PCA scores associated with a plusminusFit

plot.R2s: Plot of R2

plot.smc: Plotting function for Significant Multivariate Correlation Plotting function for Selectivity Ratio. Plotting function for Variable Importance in the Projection

plot.wrtpls: Plots of the Output of a Permutation Distribution for an...

plsFit: Partial Least Squares Regression

plusMinusDat: plusMinusDat data set PlusMinus (Mas-o-Menos)

plusminusFit: Plus-Minus (Mas-o-Menos) Classifier

plusminus.loo: Leave-one-out routine for 'plusminus' objects

predict.mvdareg: Model Predictions From a plsFit Model

print.mvdalab: Print Methods for mvdalab Objects

print.plusminus: Print Methods for plusminus Objects

proCrustes: Comparison of n-point Configurations vis Procrustes Analysis

R2s: Cross-validated R2, R2 for X, and R2 for Y for PLS models

ScoreContrib: Generates a score contribution plot

scoresplot: 2D Graph of the scores

SeqimputeEM: Sequential Expectation Maximization (EM) for imputation of...

smc: Significant Multivariate Correlation

smc.acfTest: Test of the Residual Significant Multivariate Correlation...

sr: Selectivity Ratio

T2: Generates a Hotelling's T2 Graph

vip: Variable Importance in the Projection BCa Summaries for the weights of an mvdareg object

weights: Extract Summary Information Pertaining to the Bootstrapped...

weightsplot: Extract Graphical Summary Information Pertaining to the...

weightsplot2D: Extract a 2-Dimensional Graphical Summary Information... Weight Randomization Test PLS

Xresids: Generates a Graph of the X-residuals

XresidualContrib: Generates the squared prediction error contributions and...

y.loadings: Extract Summary Information Pertaining to the y-loadings Extract Summary Information Pertaining to the y-loadings


acfplot Man page
ap.plot Man page
bca.cis Man page Man page
BiPlot Man page
boot.plots Man page Man page
coefficients.mvdareg Man page
coefficientsplot2D Man page
coef.mvdareg Man page
coefsplot Man page
College Man page
contr.niets Man page
ellipse.mvdalab Man page
imputeBasic Man page
imputeEM Man page
imputeQs Man page
imputeRough Man page
introNAs Man page
jk.after.boot Man page Man page
loadings.mvdareg Man page
loadingsplot Man page
loadingsplot2D Man page
mewma Man page
model.matrix.mvdareg Man page
MVcis Man page
MVComp Man page
mvdaboot Man page
mvdalab Man page
mvdalab-package Man page
mvdaloo Man page
mvdareg Man page
mvrnormBase.svd Man page
mvrnorm.svd Man page
my.dummy.df Man page
no.intercept Man page
pcaFit Man page
pca.nipals Man page
PE Man page
Penta Man page
perc.cis Man page
plot.cp Man page
plot.mvcomp Man page
plot.mvdapca Man page
plot.mvdareg Man page
plot.plusminus Man page
plot.R2s Man page
plot.smc Man page Man page Man page
plot.wrtpls Man page
plsFit Man page
plusMinusDat Man page Man page
plusminusFit Man page
plusminus.loo Man page
predict.mvdareg Man page
print.empca Man page
print.mvcomp Man page
print.mvdapca Man page
print.mvdareg Man page
print.npca Man page
print.plusminus Man page
print.proC Man page
print.R2s Man page
print.roughImputation Man page
print.seqem Man page
print.smc Man page Man page Man page
proCrustes Man page
R2s Man page
ScoreContrib Man page
scoresplot Man page
SeqimputeEM Man page
smc Man page
smc.acfTest Man page
smc.error Man page
smc.modeled Man page
sr Man page
sr.error Man page
sr.modeled Man page
summary.mvdareg Man page
summary.mvdareg.default Man page
summary.plusminus Man page
summary.plusminus.default Man page
T2 Man page
vip Man page Man page Man page
weights.mvdareg Man page
weightsplot Man page
weightsplot2D Man page Man page
Xresids Man page
XresidualContrib Man page
y.loadings Man page Man page


R/acfplot.R R/coef.mvdareg.R R/plot.mvcomp.R R/model.matrix.mvdareg.R R/imputeBasic.R R/XresidualContrib.R R/loadings.mvdareg.R R/plot.wrtpls.R R/loadingsplot.R R/vip.R R/Xresids.R R/print.npca.R R/weightsplot.R R/plot.plusminus.R R/T2.R R/weights.mvdareg.R R/coefficients.mvdareg.R R/MVcis.R R/print.empca.R R/loadingsplot2D.R R/print.seqem.R R/print.proC.R R/summary.plusminus.R R/plot.R2s.R R/my.dummy.df.R R/print.mvdareg.R R/print.mvdapca.R R/imputeRough.R R/ R/ R/smc.R R/mewma.R R/ R/no.intercept.R R/proCrustes.R R/R2s.R R/pcaFit.R R/sr.R R/pca.nipals.R R/plusminus.loo.R R/smc.acfTest.R R/ R/summary.mvdareg.R R/mvdaboot.R R/imputeQs.R R/introNAs.R R/SeqimputeEM.R R/boot.plots.R R/ap.plot.R R/weightsplot2D.R R/BiPlot.R R/y.loadings.R R/jk.after.boot.R R/PE.R R/MVComp.R R/imputeEM.R R/predict.mvdareg.R R/plot.mvdapca.R R/mvrnorm.svd.R R/plot.mvdareg.R R/bca.cis.R R/perc.cis.R R/plusminusFit.R R/ R/coefsplot.R R/scoresplot.R R/contr.niets.R R/plot.cp.R R/ScoreContrib.R R/mvdalab.R R/plsFit.R R/print.plusminus.R R/ R/mvrnormBase.svd.R R/ellipse.mvdalab.R R/ R/ R/coefficientsplot2D.R R/mvdaloo.R
man/loadingsplot.Rd man/MVcis.Rd man/imputeBasic.Rd man/MVComp.Rd man/proCrustes.Rd man/my.dummy.df.Rd man/plot.mvcomp.Rd man/coefficients.Rd man/SeqimputeEM.Rd man/vip.Rd man/coef.mvdareg.Rd man/ man/print.mvdalab.Rd man/introNAs.Rd man/plot.cp.Rd man/weightsplot.Rd man/BiPlot.Rd man/imputeRough.Rd man/mvdaloo.Rd man/XresidualContrib.Rd man/predict.mvdareg.Rd man/y.loadings.Rd man/ man/mvdaboot.Rd man/no.intercept.Rd man/sr.Rd man/jk.after.boot.Rd man/print.plusminus.Rd man/ScoreContrib.Rd man/plot.R2s.Rd man/coefsplot.Rd man/ man/contr.niets.Rd man/plot.mvdareg.Rd man/T2.Rd man/smc.Rd man/College.Rd man/coefficientsplot2D.Rd man/plot.wrtpls.Rd man/PE.Rd man/mvdalab-package-title.Rd man/plusMinusDat.Rd man/ man/plot.smc.Rd man/ man/loadings.Rd man/scoresplot.Rd man/model.matrix.mvdalab.Rd man/mvrnorm.svd.Rd man/imputeEM.Rd man/ap.plot.Rd man/boot.plots.Rd man/acfplot.Rd man/Xresids.Rd man/plot.plusminus.Rd man/weights.Rd man/plusminus.loo.Rd man/plusminusFit.Rd man/smc.acfTest.Rd man/imputeQs.Rd man/Penta.Rd man/R2s.Rd man/ man/plsFit.Rd man/perc.cis.Rd man/weightsplot2D.Rd man/ man/bca.cis.Rd man/mewma.Rd man/ man/loadingsplot2D.Rd man/pca.nipals.Rd man/ man/pcaFit.Rd man/ellipse.mvdalab.Rd
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