plot.Mclust {mclust} | R Documentation |
Plot model-based clustering results: BIC, classification, uncertainty and (for one- and two-dimensional data) density.
## S3 method for class 'Mclust': plot(x, data = NULL, what = c("BIC", "classification", "uncertainty", "density"), dimens = c(1,2), xlab = NULL, ylim = NULL, legendArgs = list(x = "bottomright", ncol = 2, cex = 1), identify = TRUE, ...)
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.
|
dimens |
A vector of length 2 giving the integer dimensions of the
desired coordinate projections for multivariate data. The default is
c(1,2) , in which the first dimension is plotted against the second.
|
xlab |
Optional label for the horizontal axis of the BIC plot. |
ylim |
Optiomnal limits for the vertical axis of the BIC plot. |
legendArgs |
Arguments to pass to the legend function. Set to NULL
for no legend.
|
identify |
A logical variable indicating whether or not to add a title to the plot identifying the dimensions used. |
... |
Other graphics parameters. |
For more flexibility in plotting, use mclust1Dplot
,
mclust2Dplot
, surfacePlot
, coordProj
, or
randProj
.
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.
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.
Mclust
,
mclust1Dplot
,
mclust2Dplot
,
surfacePlot
,
coordProj
,
randProj
## Not run: plot(Mclust(precip),precip) plot(Mclust(faithful),faithful) plot(Mclust(iris[,-5]),iris[,-5]) ## End(Not run)