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Marcio · (This post was last modified: 03-31-2015 03:07 PM by Marcio.)

(03-30-2015 10:07 PM)salvomic Wrote: doing so, I get a logistic as 1.1177/(1+0.6269*e^(-0.1929*X)) and it is very close to the observed data. The asymptote should be about 1.1177 (A)...
This curve seems to fit to my data better than the Gompertz (but a book of mine write that those data are from Gompertz curve...)
manually (empirically) I get for Gompertz A=1.1177, B=0.44, C=.14, but also so, Logistic is a little more close to the data...
Now I can see it in Statistic 2var (also if seems don't fit well, but I now can see who rules A,B,C: my program or ...Statistic? in fact they seem to use the same data, A, B, C ...)

The correct values for A, B and C are 1.151, 0.5191 and 0.1509 respectively. For those, R^2 = 0.9916.

Let me know if you still need the program. I will have to edit it to make it more user-friendly.

And yes, the curves are indeed very similar but only for that region your data covers, outside that area the functions behave differently, that means that the estimates you found for A, B and C using the logistic fit might not be the best for extrapolation.

Marcio