![]() When you do the fit to the equation y0 + A*y^x, you should constrain y0 to 0 and allow both A and x to vary. * In Igor Pro, you can constrain a fitting coefficient or allow it to vary. Here are a few comments on a more tutorial approach. * Using IP, the uncertainties in the fitting coefficients are directly quoted after the coefficients? What are the uncertainties on the fitting coefficients in KG? How confident are you in your coefficient -0.25064 using KG, and why did you fix the coefficient in IP to be exactly -0.24535 (as near as I can tell)? * Why are the fitting coefficients different when KG and IP should be using the same methods? What else is different between these two fitting tests? Here are some questions in that direction. I understand the methods in IP and completely trust their robustness, so I would say your results in KG are wrong. By fixing y0 results seem to be good.Īck, pooh! The graphs show, your results in KG are different from those you got in IP. Johnweeks, Your results are closed to those givent by KGraph. For fitting methods I don't know much ! In KGraph the user manual is marked : "Least Squares Curve Fits" and "Levenberg-Marquardt algorithm". Can you give some more details about the problem you have? What equation did you fit in Kaleidagraph? How did you do the fit in Igor? What was the result? What, in detail, do you think is wrong with the result?įor basic functions like power law there is no problem with KGraph. V_chisq= 1.261e-05 V_npnts= 17 V_numNaNs= 0 V_numINFs= 0 Ĭoefficient values ± one standard deviation
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