cmb.plot {cmbClust} | R Documentation |
Graphic display for the results of conditional mixture modeling and model-based clustering
Description
cmb.plot
demonstrates the clustering results of functions cmb.em
and cmb.search
. A graph with a combination of pairwise scatter plot for data points, pairwise contour plot of estimated mixture density, and pairwise regression curves is produced.
Usage
cmb.plot(obj, allcolors = NULL, allpch = NULL, lwd = 1, cex.text = 1, cex.point = 0.6,
mar = c(0.6,0.6,0.6,0.6), oma = c(3.5,3.5,2.5,14), nlevels = 30)
Arguments
obj |
output object of the function |
allcolors |
colous of clusters (length K) |
allpch |
styles of data points in clusters (length K) |
lwd |
line width, a positive number, defaulting to 1 |
cex.text |
magnification of labels and titles, defaulting to 1 |
cex.point |
magnification of plotting symbols, defaulting to 0.6 |
mar |
margin sizes of plots in lines of text (length 4) |
oma |
outer margin sizes of a pairwise plot in lines of text (length 4) |
nlevels |
number of contour levels, defaulting to 30 |
Value
This function generates a graphic.
Examples
set.seed(4)
K <- 3
l <- 2
x <- as.matrix(iris[,-5])
# Run EM algorithm for fitting a conditioning mixture model
obj <- cmb.em(x = x, order = c(1,2,3,4), l, K, method = "stepwise",
silent = TRUE, Parallel = FALSE)
cmb.plot(obj)
[Package cmbClust version 0.0.1 Index]