PLSbiplot1 (version 0.1)

PLS.biplot.area: The Partial Least Squares (PLS) biplot with triangles for estimating the Partial Least Squares Regression (PLSR) coefficients

Description

Takes in a set of predictor variables and a set of response variables and produces a PLS biplot, but with rotated coefficient points.

Usage

PLS.biplot.area(X, Y, algorithm = NULL, ax.tickvec.X = NULL, ax.tickvec.Y = NULL, base.tri, bi.value, ...)

Arguments

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

base.tri

The desired Y-variable axis to use as the base for the triangle

bi.value

The desired rotated coefficient points (bi) to approximate

...

Other arguments. Currently ignored

Value

The PLS biplot of D=[X Y] with rotated coefficient points

Examples

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")))
#with 1 triangle
PLS.biplot.area(X, Y, algorithm=mod.SIMPLS, ax.tickvec.X=c(8,5,5,5,5),
ax.tickvec.Y=c(5,10,5,6,7,10), base.tri=3, bi.value=4)
#with 4 triangles
PLS.biplot.area(X, Y, algorithm=mod.SIMPLS, ax.tickvec.X=c(8,5,5,5,5),
ax.tickvec.Y=c(5,10,5,6,7,10), base.tri=2, bi.value=c(1,2,3,4,5))