Dear all,we just realized something. Sarah's distance function - indeed -
calculates mahalanobis distance very well. However, it uses the
observed variance-covariance matrix by default.
What we actually need (sorry for not stating it clearly in to be able to
specify which variance-covariance matrix
Hi Frank,
If the way distance() calculates the Mahalanobis distance meets your
needs other than the covariance specification, you can tweak that
_very_ easily. If you use fix(distance) at the command line, you can
edit the source.
change the first line to:
function (x, method = "euclidean", icov)
distance() from the ecodist package will calculate Mahalanobis distances.
Sarah
--
Sarah Goslee
http://www.functionaldiversity.org
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http:
Dear all,
We have a data frame x with n people as rows and k variables as columns.
Now, for each person (i.e., each row) we want to calculate a distance
between him/her and EACH other person in x. In other words, we want to
create a n x n matrix with distances (with zeros in the diagonal).
Howeve
4 matches
Mail list logo
