| plot.mclustBIC {mclust} | R Documentation |
Plots the BIC from mclust modeling via function mclustBIC.
plot.mclustBIC(x, G = NULL, modelNames = NULL, symbols = NULL, colors = NULL,
ylim = NULL, legendArgs = list(x="bottomright", ncol=2, cex=1),
CEX = 1, ...)
x |
Output from mclustBIC.
|
G |
One or more numbers of components corresponding to models fit in x.
The default is to plot the BIC for all of the numbers of components fit.
|
modelNames |
One or more model names corresponding to models fit in x.
The default is to plot the BIC for all of the models fit.
|
symbols |
Either an integer or character vector assigning a plotting symbol to each
unique class in classification. Elements in colors
correspond to classes in order of appearance in the sequence of
observations (the order used by the function unique).
The default is given is .Mclust\$classPlotSymbols.
|
colors |
Either an integer or character vector assigning a color to each
unique class in classification. Elements in colors
correspond to classes in order of appearance in the sequence of
observations (the order used by the function unique).
The default is given is .Mclust\$classPlotColors.
|
ylim |
Limits for the vertical axis of the BIC plot. |
legendArgs |
Arguments to pass to the legend function. Set to NULL
for no legend.
|
CEX |
A scalar controling the size of the splot symbols. |
... |
Other graphics parameters. |
A plot of the BIC values for the models specified in the
modelNames argument.
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 for R: Normal Mixture Modeling and Model-Based Clustering, Technical Report no. 504, Department of Statistics, University of Washington.
## Not run: plot(mclustBIC(precip), legendArgs = list(x = "bottomleft")) plot(mclustBIC(faithful)) plot(mclustBIC(iris[,-5])) ## End(Not run)