```
# NOT RUN {
irisBIC <- mclustBIC(iris[,-5])
irisBIC
plot(irisBIC)
# }
# NOT RUN {
subset <- sample(1:nrow(iris), 100)
irisBIC <- mclustBIC(iris[,-5], initialization=list(subset = subset))
irisBIC
plot(irisBIC)
irisBIC1 <- mclustBIC(iris[,-5], G=seq(from=1,to=9,by=2),
modelNames=c("EII", "EEI", "EEE"))
irisBIC1
plot(irisBIC1)
irisBIC2 <- mclustBIC(iris[,-5], G=seq(from=2,to=8,by=2),
modelNames=c("VII", "VVI", "VVV"), x= irisBIC1)
irisBIC2
plot(irisBIC2)
# }
# NOT RUN {
nNoise <- 450
set.seed(0)
poissonNoise <- apply(apply( iris[,-5], 2, range), 2, function(x, n)
runif(n, min = x[1]-.1, max = x[2]+.1), n = nNoise)
set.seed(0)
noiseInit <- sample(c(TRUE,FALSE),size=nrow(iris)+nNoise,replace=TRUE,
prob=c(3,1))
irisNdata <- rbind(iris[,-5], poissonNoise)
irisNbic <- mclustBIC(data = irisNdata, G = 1:5,
initialization = list(noise = noiseInit))
irisNbic
plot(irisNbic)
# }
```

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