Have you tried Gower dissimilarity or Sammon mapping? Gower dissimilarity is in the cluster package, under the 'daisy' method. Sammon mapping is in the MASS package, under the sammon method.
You may need to redo the dissimilarity matrix with Gower/daisy first, then Sammon. Keep in mind that the low dimensional representation is non-metric. Your other option is to use 'imputed' distances, typically the mean values of the KNN of a missing value. This is often used in micro-array analyses of gene interactions. The package/method is 'impute'. Of course, make sure that whatever method you use is appropriate for your data. Best, -Justin On Wed, Mar 19, 2008 at 12:43 PM, Loic Thibaut <[EMAIL PROTECTED]> wrote: > Dear David, > > you asked this question a while ago on the R mailing list and got no > answer. I have the same problem and was wondering if you had found a > solution > > Cheers > > Loic > > Loic Thibaut, PhD candidate, > ARC Centre of Excellence for Coral Reef Studies, > School of Marine Biology, James Cook University, > Townsville, > Qld, 4811, Australia. > Tel + 61 747 815 735, Fax: + 61 747 251 570, email: > [EMAIL PROTECTED] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Justin Donaldson PhD Candidate, Informatics Indiana University Department of Human Computer Interaction Eigenmann Hall 1900 E.10th Street, Room 931 Bloomington, IN 47406 [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
