Dear Giorgio,
Fixed Point Clustering is somewhat related to the mean shift algorithm,
see fixmahal in the package fpc and the references given there (note that
this is for overlapping clustering, not partitioning).
Another potentially useful method could be dbscan, as well implemented in
fpc.
mclust offers Gaussian mixtures with a uniform "noise" component (may
make
sense after transforming your variables).
trimcluster has trimmed k-means, if you look for spherical clusters and
the problem with normality is basically outliers or heavy tails.
You may also have a look at pam/clara in package cluster.
Best regards,
Christian
On Thu, 5 Nov 2009, giorgio.arcara at unipd.it wrote:
> Hello,
>
> I need to run an unsupervised clustering analysis on several non normal
> variables.
> I think that mean shift algorithm fit perfectly my needs.
> Is there a package that run this kind of analysis?
>
> Is there any other non parametric cluster analysis that you would suggest
me?
>
> Thank you in advance
>
>
> --
> Giorgio Arcara
>
> Ph.D. student in Psychobiology
> University of Padova
> Department of General Psychology
> Via Venezia 8
> 35131 Padova, Italy
> e-mail: giorgio.arcara at unipd.it
> Tel. +39 049 8276957
>
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>
*** --- ***
Christian Hennig
University College London, Department of Statistical Science
Gower St., London WC1E 6BT, phone +44 207 679 1698
chrish at stats.ucl.ac.uk, www.homepages.ucl.ac.uk/~ucakche