Robert Kern wrote: > robert wrote: >> Is there a ready made function in numpy/scipy to compute the correlation >> y=mx+o of an X and Y fast: >> m, m-err, o, o-err, r-coef,r-coef-err ?
> scipy.optimize.leastsq() can be told to return the covariance matrix of the > estimated parameters (m and o in your example; I have no idea what you think > r-coeff is). Ah, the correlation coefficient itself. Since correlation coefficients are weird beasts constrained to [-1, 1], standard gaussian errors like you are expecting for m-err and o-err don't apply. No, there's currently no function in numpy or scipy that will do something sophisticated enough to be reliable. Here's an option: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=155684 -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco -- http://mail.python.org/mailman/listinfo/python-list
