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From: Steve Schmerler <elcorto@gm...>  20070830 13:48:41

Wolfgang Kerzendorf wrote: > I know this is not completely matplotlib related but perhaps you can > help me none the less: > I want to fit a curve to a set of data. It's a very easy curve: y=ax+b. > But I want errors for a and b and not only the rms. Is that possible. > What tasks do you recommend for doing that. > Thanks in advance > Wolfgang > from http://mathworld.wolfram.com/LeastSquaresFitting.html: (but here: y = a*x+b, so a <> b)! For the standard errors on a and b: n = float(len(x)) xm = mean(x) ym = mean(y) SSxx = dot(x,x)  n*xm**2.0 SSyy = dot(y,y)  n*ym**2.0 SSxy = dot(x,y)  n*xm*ym r = sqrt(SSxy**2.0 / (SSxx*SSyy)) s = sqrt((SSyy  (SSxy**2.0 / SSxx)) / (n2.0)) sea = s / sqrt(SSxx) seb = s * sqrt(1.0/n + (xm**2.0 / SSxx)) The values of sea, seb agree with gnuplot's "Asymptotic Standard Error".  cheers, steve Random number generation is the art of producing pure gibberish as quickly as possible. 