demo/sec3.2_ex1.R

In snoweye/MixSim: Simulating Data to Study Performance of Clustering Algorithms

### Example for Section 3.2
data("iris", package = "datasets")
p <- ncol(iris) - 1
id <- as.integer(iris[, 5])
K <- max(id)

# estimate mixture parameters
Pi <- prop.table(tabulate(id))
Mu <- t(sapply(1:K, function(k){ colMeans(iris[id == k, -5]) }))
S <- sapply(1:K, function(k){ var(iris[id == k, -5]) })
dim(S) <- c(p, p, K)

overlap(Pi = Pi, Mu = Mu, S = S)