PCA principal component analysis

Warnes, Gregory R gregory_r_warnes at groton.pfizer.com
Fri Apr 18 12:38:41 EDT 2003


- As others have noted, the correct URL for R is http://www.r-project.org.

- The 'Rpy' (http://rpy.sourceforge.net) interface between R and Python is
more reliable and better supported than the 'RSPython' interface.     I use
rpy to provide a SOAP interface to R
(http://software.biostat.washington.edu/statsoft/snake/RSOAP) and on top of
that I've build an interface between R and Zope
(http://software.biostat.washington.edu/RSessionDA).

- Finally, there are several different functions available for PCA.  I use
the 'prcomp' function from the 'mva' package, which is included in the R
distribution.

> -----Original Message-----
> From: Suchandra Thapa [mailto:ssthapa at classes.cs.uchicago.edu]
> Sent: Thursday, April 10, 2003 7:30 PM
> To: python-list at python.org
> Subject: Re: PCA principal component analysis
> 
> 
> sebastien <s.thuriez at laposte.net> wrote:
> > Is there any PCA analysis tools for python ?
> > If it does, do you have any idea on how well it would scale ?
> > 
> > I have already seen PyClimate (but it is not available for Windows
> > which will be one of the target). Is there some LAPACK like 
> packages ?
> 
> Have you considered using R (www.r-project.com) and RS/Python
> (http://www.omegahat.org/RSPython/).  R is a statistical 
> programming language
> with libraries to handle most common statistical methods.  
> Using RS/Python
> you can create R objects, populate them, and pass them into R 
> functions within
> python or vice versa.
> 
> -- 
> --------------------------------------------------------------
> --------------
> Suchandra Thapa                       
> s-thapa-11 at NOSPAMalumni.uchicago.edu  
> --------------------------------------------------------------
> --------------
> -- 
> http://mail.python.org/mailman/listinfo/python-list
> 


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