At the risk of uttering a heresy, are you bound to Python for this? I bet you could find a C library that will work well, plus it is not a hard algorithm to code yourself. I am pretty sure I have used a numerical recipes algorithm for regression in my distant past.
Also I can't help thinking the idea of forcing your regression fit through the origin is a of a bit strange thing to do. Do you want it to pass through the origin for visualisation purposes? What if the origin is not a statistically valid place for the regression fit to pass through? On Mon, Jun 16, 2008 at 9:25 PM, Charles R Harris <[EMAIL PROTECTED]> wrote: > > > On Mon, Jun 16, 2008 at 1:47 PM, Chandler Latour <[EMAIL PROTECTED]> > wrote: > >> Yes, exactly what I meant. >> > > Polyfit just fits polynomials, there is no way of fixing the constant to > zero. Your best bet is to use linalg.lstsq directly to fit the function you > want. > > Chuck > > > > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > >
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