Hi.
If you are using the function
a * Math.pow(t, b) * Math.exp(-c * t)
the gradient is:
{ Math.pow(t, b) * Math.exp(-c * t),
a * Math.log(t) * Math.pow(t, b) * Math.exp(-c * t),
-a * t Math.pow(t, b) * Math.exp(-c * t) }
> // No idea what goes here. Nothing seems to work.
Well, the gradient (partial derivatives w.r.t the parameters) is the thing
that will work; the attached figure shows the data and the function that
fits it with
a = 1.097378664278161
b = 0.4273818336149512
c = 0.01457006142420487
>
> a, b and c for this example should be: A: 1.0782 B: 0.4583 C: 0.0166
The fit is slightly better with the values found by "CurveFitter"
(the "LevenbergMarquardt" algorithm actually).
Regards,
Gilles
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