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Robust linear least squares


Hi all,

I just committed a significant chunk of code related to robust linear regression into GSL and mainly wanted to update the other developers and any other interested parties. The main idea here is that ordinary least squares is very sensitive to data outliers, and the robust algorithm tries to identify and downweight outlier points so they don't drastically affect the model. I think this is something that has been needed in gsl for a while.

I've been developing the code for a while and have been using it successfully in my own work, and also validated it pretty extensively against the matlab implementation. I still need to make some automated tests for it which I should get to next week.

In the meantime, the code is very usable and working so feel free to try it out.

Patrick


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