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MathGroup Archive 2012

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Re: nonlinearmodelfit problem

  • To: mathgroup at smc.vnet.net
  • Subject: [mg126105] Re: nonlinearmodelfit problem
  • From: "Dan O'Brien" <danobrie at gmail.com>
  • Date: Wed, 18 Apr 2012 03:52:30 -0400 (EDT)
  • Delivered-to: l-mathgroup@mail-archive0.wolfram.com
  • References: <jm4vr2$2j0$1@smc.vnet.net> <201204171002.GAA08442@smc.vnet.net>

I have had the same sort of problems.  How have you set up your 
simultaneous fit?  If it is set up so that your data is in the form

{{1,x11,y11},{1,x12,y12}......{2,x2n,y2n}}

where the first index is for the dataset (1 or 2)
and your function is set up with kroneckerdelta

nlm[dataset,x,parameters]:=KroneckerDelta[dataset-1]nlm1[parameters]+KroneckerDelta[dataset-2]nlm2[parameters]

Then you could use the Weights option in NonlinearModelFit

Weights->(If[#1==2,100000,1]&) (if the larger ranged dataset is dataset 1)

-Dan

On 4/17/2012 5:02 AM, M.Roellig wrote:
> On Thursday, April 12, 2012 12:16:02 AM UTC+2, L. Mattera wrote:
>> Hi
>> my name is Lorenzo Mattera, I am using since a short time Mathematica.
>> I am trying to solve a fitting problem where two sets of data have to be
>> fitted by two models depending on the same parameters.
>> I found very helpful the suggestions reported at
>> http://forums.wolfram.com/mathgroup/archive/2011/Sep/msg00555.html (and
>> references therein) so that I was able to
>> produce a working procedure. However, I have a "small" problem:
>> the two set of data have quite different weights as one is in the
>> 0-100000 range while the other is in the 0-1 range so that one of the two is
>> irrelevant in the fitting procedure.
>> It seems to me that NonlinearModelFit minimizes the sum of the squared
>> residuals,
>> any way to minimize the squared  normalized residuals?
>> Perhaps is one of the options, but so far I could not find it.
>> Tank you for the help
>> best regards
>> L. Mattera
> Hi,
>
> you could try to fit in the logarithmic domain.
>
> Markus
>



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