

Least squares polynomial fitting in Python, written so I can understand it - pingswept
http://pingswept.org/2009/01/24/least-squares-polynomial-fitting-in-python/

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lowkey
Want more, please. Seriously, where can I find more great blog posts like this
one. It was meaty, yet still clear and concise. It covered a super-valuable
technique in sufficient detail and even included sample python code.
Brilliant.

We are doing some device specific characterization and calibration work at my
LED lighting startup, which is why I found the post so relevant. However,
least-squares polynomial curve fitting techniques have immensely broad
application in a variety of fields. Can't wait for the follow up. (Man, I'm
such a geek)

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pingswept
Thanks.

That post took at least 10 hours over the past few weeks to write; it's
gratifying to know you found it useful. The next one will probably be on
regularized least squares (i.e. choosing an x that is close to optimal and
also small, so it behaves well in later calculations).

You might also look at Stephen Boyd's videos on linear estimation:
<http://www.youtube.com/view_play_list?p=06960BA52D0DB32B>

I think least squares is covered in lectures 5 and 6.

