Plots for model-based clustering results, such as BIC, classification, uncertainty and density.

# S3 method for Mclust
plot(x, what = c("BIC", "classification", "uncertainty", "density"),
dimens = NULL, xlab = NULL, ylab = NULL,
addEllipses = TRUE, main = FALSE, ...)

## Arguments

x Output from Mclust. A string specifying the type of graph requested. Available choices are: "BIC"plot of BIC values used for choosing the number of clusters. "classification" =a plot showing the clustering. For data in more than two dimensions a pairs plot is produced, followed by a coordinate projection plot using specified dimens. Ellipses corresponding to covariances of mixture components are also drawn if addEllipses = TRUE. "uncertainty"a plot of classification uncertainty. For data in more than two dimensions a coordinate projection plot is drawn using specified dimens. "density"a plot of estimated density. For data in more than two dimensions a matrix of contours for coordinate projection plot is drawn using specified dimens. If not specified, in interactive sessions a menu of choices is proposed. A vector of integers specifying the dimensions of the coordinate projections in case of "classification", "uncertainty", or "density" plots. Optional labels for the x-axis and the y-axis. A logical indicating whether or not to add ellipses with axes corresponding to the within-cluster covariances in case of "classification" or "uncertainty" plots. A logical or NULL indicating whether or not to add a title to the plot identifying the type of plot drawn. Other graphics parameters.

## Details

For more flexibility in plotting, use mclust1Dplot, mclust2Dplot, surfacePlot, coordProj, or randProj.

Mclust, plot.mclustBIC, plot.mclustICL, mclust1Dplot, mclust2Dplot, surfacePlot, coordProj, randProj.

## Examples

if (FALSE) {
precipMclust <- Mclust(precip)
plot(precipMclust)

faithfulMclust <- Mclust(faithful)
plot(faithfulMclust)

irisMclust <- Mclust(iris[,-5])
plot(irisMclust)
}