Maybe the onedimensional EM clustering algorithm by Francesco Bartolucci,
published 2006 could be applied. There is Matlab code available by the author
and I have implemented a version of that  in CMAT.
Wolfgang Hartmann

On Mon, Jan 26, 2009 at 1:51 PM, F. James Rohlf <[log in to unmask]> wrote:
Pierre Legendre has worked on spatially constrained clustering using
methods that may work for time also. That would be a place to start.


F. James Rohlf
Distinguished Professor, Stony Brook University

> -----Original Message-----
> From: Classification, clustering, and phylogeny estimation
> [mailto:[log in to unmask]] On Behalf Of Shannon, William
> Sent: Monday, January 26, 2009 10:45 AM
> To: [log in to unmask]
> Subject: time series clustering
> I have a new project that is intriguing and offers data I have never
> tried to cluster.
> The question is whether there are hiv/aids patients treated
> differently according to their medicaid procedure codes (what was
> done to them). Procedures occur over time so  changing the
> clustering over time would seem reasonable. Hopefully we will see
> clusters of patients form based on medical interventions given, and
> stabilize as we move forward.
> I have never done anything like this and wanted to know if anyone
> could point me in the right direction towards previously done work
> along this line.
> Thank you
> Bill Shannon, PhD
> Associate Prof. of Biostatistics in Medicine
> Washington University School of Medicine
> Director, Biostatistical Consulting Center
> 314-454-8356
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Time is not Onedimensional!
And even if it were - it would still be too difficult for me to handle.---

Wolfgang M. Hartmann  
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