PLS.GLM.biplot_SIMPLS_no.SN: The Partial Least Squares (PLS) biplot for Generalized Linear...

In PLSbiplot1: The Partial Least Squares (PLS) Biplot

Description

Takes in a set of predictor variables and a set of response variables and produces a PLS biplot for the (univariate) GLMs, with the labels of the sample points excluded.

Usage

PLS.GLM.biplot_SIMPLS_no.SN(X, y, algorithm = NULL, ax.tickvec.X = NULL,
  ax.tickvec.y = NULL, ax.tickvec.b = NULL, ...)

Arguments

X	A (NxP) predictor matrix
y	A (Nx1) response vector
algorithm	The PLS.GLM_SIMPLS algorithm
ax.tickvec.X	tick marker length for each X-variable axis in the biplot
ax.tickvec.y	tick marker length for the y-variable axis in the biplot
ax.tickvec.b	(purple) tick marker length for the y-variable axis in the biplot
...	Other arguments. Currently ignored

Value

The PLS biplot of a GLM (fitted using the SIMPLS algorithm) of D=[X y] with some parameters

Author(s)

Opeoluwa F. Oyedele and Sugnet Gardner-Lubbe

Examples

if(require(robustbase))
possum.mat
y = as.matrix(possum.mat[,1], ncol=1)
dimnames(y) = list(paste("S", 1:nrow(possum.mat), seq=""), "Diversity")
X = as.matrix(possum.mat[,2:14], ncol=13)
dimnames(X) = list(paste("S", 1:nrow(possum.mat), seq=""), colnames(possum.mat[,2:14]))
#Poisson-fitted
PLS.GLM.biplot_SIMPLS_no.SN(X, y, algorithm=PLS.GLM,
ax.tickvec.X=rep(5,ncol(X)), ax.tickvec.y=10, ax.tickvec.b=7)

PLSbiplot1 documentation built on May 2, 2019, 9:41 a.m.