numpy: code to update least squares with more observations

StackOverflow https://stackoverflow.com/questions/5952815

Question

I am looking for a numpy-based implementation of ordinary least squares that would allow the fit to be updated with more observations. Something along the lines of Applied Statistics algorithm AS 274 or R's biglm.

Failing that, a routine for updating a QR decomposition with new rows would also be of interest.

Any pointers?

No correct solution

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