Description Usage Arguments Value Author(s) Examples
Takes in a set of predictor variables and a set of response variables and produces a PLS biplot, but with no sample points names.
1 2 | PLS.biplot_no_labels(X, Y, algorithm = NULL, ax.tickvec.X = NULL,
ax.tickvec.Y = NULL, ...)
|
X |
A (NxP) predictor matrix |
Y |
A (NxM) response matrix |
algorithm |
Any of the PLS algorithms ("mod.NIPALS", "mod.KernelPLS_R", "mod.KernelPLS_L", "mod.SIMPLS") |
ax.tickvec.X |
tick marker length for each X-variable axis in the PLS biplot |
ax.tickvec.Y |
tick marker length for each Y-variable axis in the PLS biplot |
... |
Other arguments. Currently ignored |
The PLS biplot of D=[X Y] with no sample points names but with fainted tick markers and labels
Opeoluwa F. Oyedele and Sugnet Gardner-Lubbe
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | 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")))
PLS.biplot_no_labels(X, Y, algorithm=mod.SIMPLS, ax.tickvec.X=c(8,5,5,5,5),
ax.tickvec.Y=c(5,8,5,6,9,8))
#cocktail data
if(require(SensoMineR))
data(cocktail, package="SensoMineR")
X3 = as.matrix(compo.cocktail, ncol=4)
Y3 = as.matrix(senso.cocktail, ncol=13)
PLS.biplot_no_labels(X=X3, Y3, algorithm=mod.SIMPLS, ax.tickvec.X=rep(2,ncol(X3)),
ax.tickvec.Y=rep(3,ncol(Y3)))
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