mclust (version 2.1-14)

plot.Mclust: Plot Model-Based Clustering Results

Description

Plot model-based clustering results: BIC, classification, uncertainty and (for one- and two-dimensional data) density.

Usage

plot.Mclust(x, data, dimens = c(1, 2), scale = FALSE, ...)

Arguments

x

Output from Mclust.

data

The data used to produce x.

dimens

An integer vector of length two specifying the dimensions for coordinate projections if the data is more than two-dimensional. The default is c(1,2) (the first two dimesions).

scale

A logical variable indicating whether or not the two chosen dimensions should be plotted on the same scale, and thus preserve the shape of the distribution. Default: scale=FALSE

...

Further arguments to the lower level plotting functions.

Value

• Plots selected via a menu including the following options: BIC values used for choosing the number of clusters For data in more than two dimensions, a pairs plot of the showing the classification, coordinate projections of the data, showing location of the mixture components, classification, and/or uncertainty. For one- and two- dimensional data, plots showing location of the mixture components, classification, uncertainty, and or density.

References

C. Fraley and A. E. Raftery (2002a). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631. See http://www.stat.washington.edu/mclust. C. Fraley and A. E. Raftery (2002b). MCLUST:Software for model-based clustering, density estimation and discriminant analysis. Technical Report, Department of Statistics, University of Washington. See http://www.stat.washington.edu/mclust.

See Also

Mclust

Examples

data(iris)
irisMatrix <- as.matrix(iris[,1:4])
irisMclust <- Mclust(irisMatrix)

plot(irisMclust,irisMatrix)