I'm having a "duh" moment here ... I've googled and looked through my old
college text books and can't find something that I think should be easy to
find. I'm probably forgetting the proper name of the technique or something
stupid.
The basic formulas for least squares fitting of a line to a set of data are
well know. (I'm referring to the standard linear least squares fit of a
line to some data.)
I know I've seen a derivation of these formulas that allow you to
incrementally build your least squares solution as each data point comes in
(based on the current data and the past solution.) I know I've seen this
several places in my life, even recently. I'd rather not spend a week
re-deriving the formulas from scratch and testing and debugging.
Does anyone have a link or pointer to basic code or psuedo-code that
implements this incremental (recursive?) least squares approach?
Thanks in advance,
Curt.
--
Curtis Olson: http://baron.flightgear.org/~curt/
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