Thanks!

When I tried using PROC FASTCLUS, it does not return

Eigenvalues of the Covariance Matrix that PROC CLUSTER does, which gives me a good idea of the # of vectors of my correlated covariates that explains most (>=80%) of my total covariates variance. How do these two procedures differ in computational algorithm?

On Thu, Jun 18, 2009 at 1:00 PM, Dennis Fisher <dfisher@csulb.edu> wrote:

> Usually when you have that many observations you would use PROC FASTCLUS > instead. > > Dennis G. Fisher, Ph.D. > Professor and Director > Center for Behavioral Research and Services > California State University, Long Beach > 1090 Atlantic Avenue > Long Beach, CA 90813 > tel: 562-495-2330 x121 > fax: 562-983-1421 > http://www.csulb.edu/centers/cbrs > > -----Original Message----- > From: SAS(r) Discussion [mailto:SAS-L@LISTSERV.UGA.EDU] On Behalf Of OR > Stats > Sent: Thursday, June 18, 2009 10:40 AM > To: SAS-L@LISTSERV.UGA.EDU > Subject: PROC CLUSTER... slow > > Hello: I have some 2,000 records for which I am running PROC CLUSTER on 7 > variables. After almost a full 24h, it still was not done. I am running > XP > with E5440 @ 2.83 GHz 2.83 GHz at 3.25 GB of RAM. Does anyone know why it > is so slow? Thx so much!! > >