EMCluster (version 0.2-10)

Plot Projection and Contour: Plot Contour

Description

The function plots multivariate data on 2D plane with contour. Typically, the contour is built via projection pursuit or SVD algorithms, such as project.on.2d().

Usage

plotppcontour(da, Pi, Mu, S, class, class.true = NULL, n.grid = 128,
    angle = 0, xlab = "", ylab = "", main = "")

Arguments

da

a projected data matrix, dimension \(n\times 2\).

Pi

proportion, length \(K\).

Mu

the projected centers of cluster, dimension \(K\times 2\).

S

projected matrices of dispersion, dimension \(p\times p \times K\).

class

id of classifications, length \(n\).

class.true

ture id of classifications if available, length \(n\).

n.grid

number of grid points.

angle

a rotation angle (\(0\) to \(2\pi\)).

xlab

an option for plot() function.

ylab

an option for plot() function.

main

an option for plot() function.

Value

A 2D projection plot is returned.

Details

This function plots projection output of project.on.2d().

da, Mu, and S are projected by some projection matrices obtained via SVD or projection pursuit algorithms. The projection is made on a 2D plane in the direction in which clusters of data x are most distinguishable to visualize.

References

http://maitra.public.iastate.edu/

See Also

project.on.2d().

Examples

Run this code
# NOT RUN {
library(EMCluster, quietly = TRUE)
library(MASS, quietly = TRUE)
set.seed(1234)

### Crabs.
x <- as.matrix(crabs[, 4:8])
ret <- init.EM(x, nclass = 4, min.n = 20)
ret.proj <- project.on.2d(x, ret)

### Plot.
pdf("crabs_ppcontour.pdf", height = 5, width = 5)
plotppcontour(ret.proj$da, ret.proj$Pi, ret.proj$Mu, ret.proj$S,
              ret.proj$class, angle = pi/6, main = "Crabs K = 4")
dev.off()
# }

Run the code above in your browser using DataLab