Nonlinear Curve Fit VI keeps all initial parameters

[altenbach]

OK, we have x and y reversed.

Still, your model is very unstable and the result turns negative if x < the last parameter.

[stevensung]

I am glad to hear that we are now closer...

At this moment I am bound to this model and could not change it. The fact that it is not so stable seems to make the actual curve fitting favor the Contrained nonlinear curve fit VI, with which at least we could be able to confine range of our fit parameters.

[altenbach]

Except that the needed constraint depends on a fitting parameter, which itself is variable during fitting.