Clustering of synthetic control data in R, see http://anandnalya.com/2012/05/01/clustering-of-synthetic-control-data-in-r/

clustering.R

x <- read.table("synthetic_control.data")
cat( "read", length(x[,1]), "records.\n")

# load clustering library
library(flexclust)

# get number of clusters from user
n <- as.integer( readline("Enter number of clusters: ")) 

# run kmeans clustering on the dataset
cl1 <- cclust(x, n)

print("clustering complete")

# show summary of clustering
summary(cl1)

# plot the clusters
plot(cl1, main="Clusters")

readline("Press enter for cluster histogram")
m<-info(cl1, "size") # size of each cluster
hist(rep(1:n, m), breaks=0:n, xlab="Cluster No.", main="Cluster Plot")

readline("Press enter for a plot of distance of data points from its cluster centorid")
stripes(cl1)
print("done")