How to keep signs of input parameters fixed while using "levenberg-marquardt" algorithm for lsqcurvefit?
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If I use upper and lower bounds for my parameters, the algorithm switches to trust region method automatically. Is there any other way to just keep the signs constant during iterations?
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Matt J
on 15 Jan 2017
But why cling to Levenberg-Marquardt when it is not natural for the problem you are trying to solve? If you have bounds, why oppose MATLAB's efforts to choose a solver more appropriate for that?
Answers (1)
John D'Errico
on 15 Jan 2017
Edited: John D'Errico
on 15 Jan 2017
An easy solution is to change your model slightly using a transformation. For example, suppose you wanted to solve for coefficients of the model
y = a*x
but you wanted to ensure that a was ALWAYS positive, but you don't want to apply bound constraints? Instead solve for the coefficients of the model:
y = b^2*x
As you can see, b^2 will always be positive, so there is never a chance that b^2 will change sign on you. When you are done, just transform b back into a as
a = b^2
Yes, it is a hack. But it allows you to formulate a problem to work in the solver you want to use, without the employment of explicit bound constraints.
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