```
library(cluster)
data(animals)
plot(energy.hclust(dist(animals)))
data(USArrests)
ecl <- energy.hclust(dist(USArrests))
print(ecl)
plot(ecl)
cutree(ecl, k=3)
cutree(ecl, h=150)
## compare performance of e-clustering, Ward's method, group average method
## when sampled populations have equal means: n=200, d=5, two groups
z <- rbind(matrix(rnorm(1000), nrow=200), matrix(rnorm(1000, 0, 5), nrow=200))
g <- c(rep(1, 200), rep(2, 200))
d <- dist(z)
e <- energy.hclust(d)
a <- hclust(d, method="average")
w <- hclust(d^2, method="ward")
list("E" = table(cutree(e, k=2) == g), "Ward" = table(cutree(w, k=2) == g),
"Avg" = table(cutree(a, k=2) == g))
```

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