[SciPy-User] Least median of squares for regression in scipy?

[Skipper Seabold]

On Tue, Aug 24, 2010 at 10:16 AM,  <josef.pktd at gmail.com> wrote:
> On Tue, Aug 24, 2010 at 10:06 AM, Jorge Scandaliaris
> <jorgesmbox-ml at yahoo.es> wrote:
>>  <josef.pktd <at> gmail.com> writes:
>>
>>>
>>> scikits.statsmodels has robust linear model estimators,  rlm
>>>
>>> Josef
>>
>> Thanks, I'll check it out
>
>
> The wikipedia link for Huber loss function, and
> http://statsmodels.sourceforge.net/rlm.html might get you started.
>

This, with your other link should get you moving.  We have as of now
only M-estimators with several weighting norms
(http://statsmodels.sourceforge.net/rlm_techn1.html) and scale
estimators that are proposed in your reference.  The framework is
there for extension using iteratively reweighted least squares, if you
need to go down this route.  Let me know if any of the documentation
or code is not clear.

> It should be possible to try out different options to see which
> version can handle your outliers.
>
>
> (I'm a bit busy and don't know rlm so well, but if you have any
> questions, I could look at them tonight, or maybe Skipper is
> available. Skipper worked on RLM.)
>
> Josef
>
>>
>>
>> Jorge
>>
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