Description Usage Arguments Author(s) References See Also Examples
Graphs data projected onto the estimated subspace for modelbased clustering and classification.
1 2 3 4 5 6 
x 
An object of class 
dimens 
A vector of integers giving the dimensions of the desired coordinate projections for multivariate data. 
what 
The type of graph requested:

symbols 
Either an integer or character vector assigning a plotting symbol to each
unique mixture component. Elements in 
colors 
Either an integer or character vector assigning a color to each
unique cluster or known class. Elements in 
col.contour 
The color of contours in case 
col.sep 
The color of classification boundaries in case 
ngrid 
An integer specifying the number of grid points to use in evaluating the classification regions. 
nlevels 
The number of levels to use in case 
asp 
For scatterplots the y/x aspect ratio, see

... 
further arguments passed to or from other methods. 
Luca Scrucca
Scrucca, L. (2010) Dimension reduction for modelbased clustering. Statistics and Computing, 20(4), pp. 471484.
MclustDR
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22  mod < Mclust(iris[,1:4], G = 3)
dr < MclustDR(mod)
plot(dr, what = "evalues")
plot(dr, what = "pairs")
plot(dr, what = "scatterplot", dimens = c(1,3))
plot(dr, what = "contour")
plot(dr, what = "classification", ngrid = 200)
plot(dr, what = "boundaries", ngrid = 200)
plot(dr, what = "density")
plot(dr, what = "density", dimens = 2)
data(banknote)
da < MclustDA(banknote[,2:7], banknote$Status, G = 1:3)
dr < MclustDR(da)
plot(dr, what = "evalues")
plot(dr, what = "pairs")
plot(dr, what = "contour")
plot(dr, what = "contour", dimens = c(1,3))
plot(dr, what = "classification", ngrid = 200)
plot(dr, what = "boundaries", ngrid = 200)
plot(dr, what = "density")
plot(dr, what = "density", dimens = 2)

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