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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