Mahalanobis distance in R

Question

I have found the mahalanobis.dist function in package StatMatch (http://cran.r-project.org/web/packages/StatMatch/StatMatch.pdf) but it isn\'t doing exactly what I want. It

Answer 1

You can wrap the function stats::mahalanobis as bellow to output a mahalanobis distance matrix (pairwise mahalanobis distances):

# x - data frame
# cx - covariance matrix; if not provided, 
#      it will be estimated from the data
mah <- function(x, cx = NULL) {
  if(is.null(cx)) cx <- cov(x)
  out <- lapply(1:nrow(x), function(i) {
    mahalanobis(x = x, 
                center = do.call("c", x[i, ]),
                cov = cx)
  })
  return(as.dist(do.call("rbind", out)))
}

Then, you can cluster your data and plot it, for example:

# Dummy data
x <- data.frame(X = c(rnorm(10, 0), rnorm(10, 5)), 
                Y = c(rnorm(10, 0), rnorm(10, 7)), 
                Z = c(rnorm(10, 0), rnorm(10, 12)))
rownames(x) <- LETTERS[1:20]
plot(x, pch = LETTERS[1:20])

# Comute the mahalanobis distance matrix
d <- mah(x)
d

# Cluster and plot
hc <- hclust(d)
plot(hc)