PDAopt: PP optimization using PDA index

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

Description

PP optimization using PDA index

Usage

PDAopt(origclass,origdata,q=1,weight=TRUE,lambda=0.1,...)

Arguments

origclass	class information vector of data
origdata	data matrix without class information
q	dimension of projection vector
weight	weight flag in PDA index
lambda	lambda in PDA index
...	arguments to be passed to methods

Details

Find the q-dimensional optimal projection using PDA projectin pursuit index

Value

indexbest maximum PDA index value

projbest optimal q-dimensional projection matrix

origclass original class information vector

origdata original data matrix without class information

References

Lee, EK, Cook, D.(2010) A Projection Pursuit Index for Large p Small n Data, Statistics and Computing, 20:381-392.

Examples

data(iris)
PDA.proj.result <- PDAopt(iris[,5],iris[,1:4],weight=TRUE,q=2,lambda=0.1)
PDA.proj.result$indexbest
PDA.proj.result$projbest

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