Hi guys and gals, Currently I'm attempting to fit the following data to the general logistic model:
[(0,0),(1,0),(2,13),(3,28),(4,48),(5,89),(6,107),(7,168),(8,188),(9,209)] The form of the logistic curve I am using is: K/(1 + a*exp(r * (t - t0)))^(1/v) with K,a,r,t0 and v being parameters, t the dependent variable. Attempting to use find_fit, I get values of: [K == 84.999999972210745, a == 126.84970317061706, r == -183.75725583987102, t0 == -124.8433024602822, v == 105.35677984548882] This is obviously wrong as K is nowhere near the right-hand asymptote in the data. Using a more bare-bones approach based on fmin, I get more realistic results of: [249.143779989,11.657027477,-0.535852892673,-0.0364250104883,0.52301206184] Since I don't get any warning messages, I don't really understand what's going wrong. Does anyone have any advice? Joal Heagney -- To post to this group, send an email to sage-devel@googlegroups.com To unsubscribe from this group, send an email to sage-devel+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/sage-devel URL: http://www.sagemath.org