cov.biplot: The covariance biplot

Description Usage Arguments Value Author(s) Examples

View source: R/AllFunctions.R

Description

Takes in a set of predictor variables and a set of response variables and produces a covariance biplot.

Usage

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cov.biplot(X, Y, ...)

Arguments

X

A (NxP) predictor matrix

Y

A (NxM) response matrix

...

Other arguments. Currently ignored

Value

The covariance biplot of X and Y

Author(s)

Opeoluwa F. Oyedele and Sugnet Gardner-Lubbe

Examples

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if(require(pls))
data(oliveoil, package="pls")
X = as.matrix(oliveoil$chemical, ncol=5)
dimnames(X) = list(paste(c("G1","G2","G3","G4","G5","I1","I2","I3","I4",
"I5","S1","S2","S3","S4","S5","S6")),
paste(c("Acidity","Peroxide","K232","K270","DK")))
Y = as.matrix(oliveoil$sensory, ncol=6)
dimnames(Y) = list(paste(c("G1","G2","G3","G4","G5","I1","I2","I3","I4",
"I5","S1","S2","S3","S4","S5","S6")),
paste(c("Yellow","Green","Brown","Glossy","Transp","Syrup")))
cov.biplot(X, Y)

#cocktail data
if(require(SensoMineR))
data(cocktail, package="SensoMineR")
X3 = as.matrix(compo.cocktail, ncol=4)
Y3 = as.matrix(senso.cocktail, ncol=13)
cov.biplot(X3,Y3)

PLSbiplot1 documentation built on May 30, 2017, 12:52 a.m.