Plots the BIC values returned by the mclustBIC
function.
# S3 method for mclustBIC
plot(x, G = NULL, modelNames = NULL,
symbols = NULL, colors = NULL,
xlab = NULL, ylab = "BIC", ylim = NULL,
legendArgs = list(x = "bottomright", ncol = 2, cex = 1, inset = 0.01),
…)
Output from mclustBIC
.
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.
One or more model names corresponding to models fit in x
.
The default is to plot the BIC for all of the models fit.
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 by mclust.options("classPlotSymbols")
.
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 by mclust.options("classPlotColors")
.
Optional label for the horizontal axis of the BIC plot.
Label for the vertical axis of the BIC plot.
Optional limits for the vertical axis of the BIC plot.
Arguments to pass to the legend
function. Set to NULL
for no legend.
Other graphics parameters.
A plot of the BIC values.
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, A. E. Raftery, T. B. Murphy and L. Scrucca (2012). mclust Version 4 for R: Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation. Technical Report No. 597, Department of Statistics, University of Washington.
# NOT RUN {
plot(mclustBIC(precip), legendArgs = list(x = "bottomleft"))
plot(mclustBIC(faithful))
plot(mclustBIC(iris[,-5]))
# }
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