Re: Re: Constraints to parameters in FindFit?
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- Subject: [mg51246] Re: [mg51227] Re: Constraints to parameters in FindFit?
- From: "Janos D. Pinter" <jdpinter at hfx.eastlink.ca>
- Date: Sun, 10 Oct 2004 01:57:17 -0400 (EDT)
- References: <email@example.com> <200410090818.EAA09667@smc.vnet.net>
- Sender: owner-wri-mathgroup at wolfram.com
Jill et al.,
In general, you do need global optimization to solve constrained model
In the monograph
I discuss several related case studies. The short tutorial book
http://www.lionhrtpub.com/books/globaloptimization.html includes a demo
example that is [sounds] very similar to Jill's model. Please also see
e.g., Globally optimized calibration of nonlinear models: techniques,
software, and applications. Optimization Methods and Software 18 (2003) (3)
At 05:18 AM 10/9/2004, Peter Valko wrote:
>For sign restiction an old trick is to use instead of paramold the
>expression Exp[paramnew] or -Exp[paramnew] in your model, and search
>for paramnew (instead of paramold).
>Jill Foley <efoley at princeton.edu> wrote in message
>news:<ck5e57$oio$1 at smc.vnet.net>...
> > Hi All,
> > I am using FindFit to fit a series of peaks to some data. I would like
> > to be able to constrain some of the parameters of my fit to correspond
> > to physical reality. For example, some peaks should have a negative
> > amplitude, others positive, where the amplitudes are the parameters
> > that Mathematica is finding in FindFit. The peaks are all very near
> > each other, so without any constraint, it is making the wrong ones
> > negative. I'd like to specify that a given parameter should always be
> > negative. I am already giving an initial guess of the proper sign, but
> > it doesn't fix the problem.
> > Please advise - Thanks!
> > Jill.
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