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NonlinearModelFit and assumptions on fit parameters

  • To: mathgroup at smc.vnet.net
  • Subject: [mg128200] NonlinearModelFit and assumptions on fit parameters
  • From: Niles <niels.martinsen at gmail.com>
  • Date: Sun, 23 Sep 2012 03:01:33 -0400 (EDT)
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  • Delivered-to: l-mathgroup@wolfram.com
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Hi

I have a set of data (x, y) that I can succesfully fit a nonlinear function to using NonlinearModelFit:


data = {{1, 1}, {2, 2}, {3, 3.2}};
fitFuncExactNoLosses[a_, b_, x_] := a*x^2 + b + x;
nlm = NonlinearModelFit[data, fitFuncExactNoLosses[a, b, x],
  {
   {a, 1},
   {b, 1}},
  x]


However, the paramter "b" comes out negative and it *must* be positive. Is there a way to utilize assumptions such that b is constrained to be grater than zero?

Best,
Niels.



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