plot.bootsPLS: Plot the frequency of selection of all variables for all the...

In bootsPLS: Bootstrap Subsamplings of Sparse Partial Least Squares - Discriminant Analysis for Classification and Signature Identification

Description

Plot the frequency of selection of all variables for all the PLS-component.

Usage

## S3 method for class 'bootsPLS'
plot(x,light,pch,col,legend.position,title, name.var=TRUE,...)

Arguments

x	Object of class ‘bootsPLS’.
light	Between 0 and 1. A lot of variables usually have a low frequency, this argument allows you to discard those from the plot. Only the variables that have a frequency higher than light on at least one component are plotted.
pch	A vector of length ncomp (argument of bootsPLS). See par for details.
col	A vector of length ncomp (argument of bootsPLS). See par for details.
legend.position	Location of the legend, see legend for more details. If set to FALSE, no legend is plotted.
title	title of the plot
name.var	If TRUE, add the name of the variables in x$data$X on the x-axis. A vector of length the number of variables can be supplied for customized names.
...	not used

Details

Plot the frequency of selection of all variables depending on the component. By default, a legend and a title are added to the plot, those can be changed/removed by changing the respective inputs.

See Also

bootsPLS

Examples

## Not run: 
data(MSC)
X=MSC$X
Y=MSC$Y
dim(X)
table(Y)


boot=bootsPLS(X=X,Y=Y,ncomp=3,many=5,kCV=5)

plot(boot)
plot(boot,light=0.3,legend.position=FALSE)
plot(boot,light=0.3,legend.position=FALSE, name.var = paste("Gene",1:ncol(X)))

## End(Not run)

bootsPLS documentation built on May 2, 2019, 2:44 a.m.