mclust (version 3.0-0)

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, what = c("BIC", "classification", 
            "uncertainty", "density"), ylimBIC = NULL,...)

Arguments

x

Output from Mclust.

data

The data used to produce x.

what

Choose one or more of: "BIC", "classification", "uncertainty". If the data dimension is less than 3, "density" can also be chosen.

ylimBIC

Limits for the vertical axis of the BIC plot.

...

Other graphics parameters.

Value

• Model-based clustering plots: BIC values used for choosing the number of clusters. For data in more than two dimensions, a pairs plot of the showing the classification, a coordinate projections of the data showing location of the mixture components, classification, and uncertainty. For one- and two- dimensional data, plots showing location of the mixture components, classification, uncertainty, and density.

References

C. Fraley and A. E. Raftery (2002). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631.

C. Fraley and A. E. Raftery (2006). MCLUST Version 3: An R Package for Normal Mixture Modeling and Model-Based Clustering, Technical Report, Department of Statistics, University of Washington.

Details

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

See Also

Mclust, mclust1Dplot, mclust2Dplot, surfacePlot, coordProj, randProj

Examples

plot(Mclust(precip),precip)

plot(Mclust(faithful),faithful)

plot(Mclust(iris[,-5]),iris[,-5])