From: Patrick Alken <patrick.alken@Colorado.EDU>
To: "gsl-discuss@sourceware.org" <gsl-discuss@sourceware.org>
Subject: Robust linear least squares
Date: Fri, 10 May 2013 22:01:00 -0000 [thread overview]
Message-ID: <518D6E3B.8080503@colorado.edu> (raw)
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
next reply other threads:[~2013-05-10 22:01 UTC|newest]
Thread overview: 6+ messages / expand[flat|nested] mbox.gz Atom feed top
2013-05-10 22:01 Patrick Alken [this message]
2013-05-12 17:56 ` Peter Teuben
2013-05-12 18:13 ` Dirk Eddelbuettel
2013-05-12 18:14 ` Patrick Alken
2013-05-24 19:23 Timothée Flutre
2013-05-24 20:12 ` Patrick Alken
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