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Re: mpcurvefit vs. a matlab fitting technique [message #61612 is a reply to message #61606]

Tue, 22 July 2008 06:12

Vince Hradil
Messages: 574
Registered: December 1999

Senior Member

On Jul 22, 5:55 am, sheilakan...@googlemail.com wrote:
>> But if I change the input even slightly eg [9.4,0.24,0.77,-1.5]
>> I get totally different values out, eg [7.7098139, 0.19333284,
>> 0.60223838, -0.85758867]
>
> Sorry, typo, this should read:
>
> But if I change the input even slightly eg [9.44,0.24,0.77,-1.5]
> I get totally different values out, eg [7.7098139, 0.19333284,
> 0.60223838, -0.85758867]

I have found the mpfit routines to be quite good at minimizing square
errors. There are a lot of "tweaks" one can use, such as step-size,
to help the routines avoid local minima - take a look at the parinfo
keyword.

I will also depend a lot on the equation that you are fitting.
Perhaps the variables are slightly "mixed", or the numerical
derivatives are ill-conditioned (is that the right term?). If
possible, one can also use analytical derivatives with the mpfit
functions, which might help.

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[Message index]

		Re: mpcurvefit vs. a matlab fitting technique By: Craig Markwardt on Wed, 23 July 2008 21:07
		Re: mpcurvefit vs. a matlab fitting technique By: R.G. Stockwell on Tue, 22 July 2008 09:46
		Re: mpcurvefit vs. a matlab fitting technique By: Vince Hradil on Tue, 22 July 2008 06:12
		Re: mpcurvefit vs. a matlab fitting technique By: sheilakanani on Tue, 22 July 2008 03:55

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