The manhattan distance and the Mahalanobis distances are
quite different. One of the main differences is that
a covariance matrix is necessary to calculate the Mahalanobis
distance, so it's not easily accomodated by dist. There
is a function in base R which does calculate the Mahalanobis
distance -- mahalanobis(). So if you pass a distance matrix
calculated by mahalanobis() to the clustering function, you'll
get what you want.
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spec...@stat.berkeley.edu
On Wed, 3 Mar 2010, Tal Galili wrote:
when you create the distance function to put into the hclust, use:
dist(x, method = "manhattan")
Tal
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On Wed, Mar 3, 2010 at 9:14 PM, naama <nw...@technion.ac.il> wrote:
How can I perform cluster analysis using the mahalanobis distance instead
of
the euclidean distance?
thank you
Naama Wolf
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