Projection On 2D {EMCluster} R Documentation

## Produce Projection on 2D

### Description

The function projects multivariate data on 2D plane which can be displayed by plotppcontour() later.

### Usage

project.on.2d(x, emobj = NULL, pi = NULL, Mu = NULL,
LTSigma = NULL, class = NULL, method = c("PP", "SVD"))


### Arguments

 x the data matrix, dimension n\times p. emobj the desired model which is a list mainly contains pi, Mu, and LTSigma, usually a returned object from init.EM. pi the mixing proportion, length K. Mu the centers of clusters, dimension K\times p. LTSigma the lower triangular matrices of dispersion, K\times p(p+1)/2. class id of classifications, length n. method either projection pursuit or singular value decomposition.

### Details

This function produces projection outputs of x and emobj.

### Value

A projection is returned which is a list contains

• da is a n \times 2 projected matrix of x.

• Pi is the original proportion emobj$pi of length K. • Mu is a K \times 2 projected matrix of emboj$Mu.

• S is a 2 \times 2 \times K projected array of emboj$LTSigma. • class is the original class id emobj$class.

• proj.mat is the projection matrix of dimension p \times 2.

### Author(s)

Wei-Chen Chen wccsnow@gmail.com and Ranjan Maitra.

### References

project.on.2d().

### Examples

## Not run:
library(EMCluster, quietly = TRUE)
set.seed(1234)

### Iris.
x <- as.matrix(iris[, 1:4])
ret <- init.EM(x, nclass = 3, min.n = 30)
ret.proj <- project.on.2d(x, ret)

### Plot.
pdf("iris_ppcontour.pdf", height = 5, width = 5)
plotppcontour(ret.proj$da, ret.proj$Pi, ret.proj$Mu, ret.proj$S,
ret.proj\$class, main = "Iris K = 3")
dev.off()

## End(Not run)


[Package EMCluster version 0.2-14 Index]