Mclust(data, minG, maxG)
1
component.9
components.sigma[,,k]
gives the covariance for the kth group in
the best model. For one-dimensional models, either a scalar giving
a common variance for the groups or a vector whose entries are the
variances for each group in the best model.Mclust
:
"E" for spherical, equal variance (one-dimensional)
"V" for spherical, variable variance (one-dimensional)
"EII": spherical, equal volume
"VII": spherical, unequal volume
"EEI": diagonal, equal volume, equal shape
"VVI": diagonal, varying volume, varying shape
"EEE": ellipsoidal, equal volume, shape, and orientation
"VVV": ellipsoidal, varying volume, shape, and orientation
Mclust
is intended to combine EMclust
and its
summary
in a simiplified one-step model-based clustering
function. The latter provide more flexibility including choice of
models.plot.Mclust
,
EMclust
data(iris)
irisMatrix <- as.matrix(iris[,1:4])
irisClass <- iris[,5]
irisMclust <- Mclust(irisMatrix)
plot(irisMclust,irisMatrix)
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