Robust statistics and optimmization from Python

[Tim Churches]

beliavsky at aol.com wrote:
> Robert Kern wrote:
> 
> <snip>
> 
>>If you find suitable
>>FORTRAN or C code that implements a particular "robust" algorithm, it
>>can probably wrapped for scipy relatively easily.
> 
> 
> An alternative would be to call R (a free statistical package) from
> Python, using something like the R/SPlus - Python Interface at
> http://www.omegahat.org/RSPython/ .

Unless you really want to call Python from R (as opposed to calling R
from Python), I strongly suggest that you use RPy (http://rpy.sf.net)
rather than RSPython. RPy is much easier to install and use and far less
buggy than RSPython.

> Many statistical algorithms,
> including those for robust statistics, have been implemented in R,
> usually by wrapping C or Fortran 77 code.

Yup, and if you really don't like the extra dependency or extra memory
requirements of R and RPy, it is often possible to port the R code back
to Python (or Numeric Python), with some effort.

Tim C