Hi,

at Blue Yonder we often use Scikit-Learn but are sometimes missing
more robust regression methods that are not based on the L2 norm.
So far I only knew Theil-Sen as a linear regression method with only a
single explanatory variable. The work of Xin Dang, Hanxiang Peng,
Xueqin Wang and Heping Zhang extend the method to n explanatory
variables. So it should perfectly fit into the sklearn.linear_model
subpackage I think. Where is the line drawn between functionality that
should go into StatsModels and into Scikit-Learn with respect to
regression methods?

Florian

On 10 January 2014 19:18, Skipper Seabold <jsseab...@gmail.com> wrote:
> Hi,
>
> There have been some implementations of Theil-Sen floating around for 
> inclusion in statsmodels, but no PRs yet. IMO it might fit in a little better 
> in statsmodels.robust than sklearn unless their are some aspects of Theil-Sen 
> I'm not familiar with.
>
> Skipper
>
> Sent from my mobile
>
>> On Jan 10, 2014, at 12:16 PM, "florian.wilh...@gmail.com" 
>> <florian.wilh...@gmail.com> wrote:
>>
>> Hi,
>>
>> I'd like to add a Theil-Sen estimator for a multiple linear regression
>> problem to Scikit-Learn as described in the paper:
>> http://home.olemiss.edu/~xdang/papers/MTSE.pdf
>> Is anyone already working on this or are there any objections
>> regarding the inclusion of a Theil-Sen estimator into Scikit-Learn?
>>
>> Best regards,
>>
>> Florian Wilhelm
>>
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