Huberplot: Huber plot

In EK-Lee/PPtreeViz: Projection Pursuit Classification Tree Visualization

Description

Huber plot for 2D data

Usage

Huberplot(origdata2D,origclass,PPmethod="LDA",weight=TRUE,r=1,
           lambda=0.5,opt.proj=TRUE,UserDefFtn=NULL,...)

Arguments

origdata2D	2-dimensional numerical data for Huber plot
origclass	class information vector of data
PPmethod	method for projection pursuit; "LDA", "PDA", "Lr", "GINI", "ENTROPY", and "UserDef"
weight	weight flag in LDA, PDA and Lr index
r	r in Lr index
lambda	lambda in PDA index
opt.proj	flag to show the best projection in the plot
UserDefFtn	User defined index function when PPmethod="UserDef"
...	arguments to be passed to methods

Details

Draw Huber plot for 2-dimensional data with various PP indices and the histogram of the projected data onto the optimal projection to explore the behavior of the projection prsuit indices

References

Lee, EK., Cook, D., Klinke, S., and Lumley, T.(2005) Projection Pursuit for Exploratory Supervised Classification, Journal of Computational and Graphical Statistics, 14(4):831-846.

Examples

data(iris)
Huberplot(iris[,1:2],iris[,5],PPmethod="LDA")

EK-Lee/PPtreeViz documentation built on May 6, 2019, 3:09 p.m.