Re: Step-function fit using leasqr

On Thu, Sep 1, 2016 at 3:21 PM, Tweety <address@hidden> wrote:

Dear all,

I am trying to fit measured data using a step function, please see the attachments. I get an error "weighted residuals are not real". Ok, additionally to a conceptual glitch I might have bad initial values but I thought Marquardt Levenberg was supposed to converge even in that case. What am I missing?

I appreciate any suggestions. I might be on the wrong track with the model function and the initial values, so if there are any better approaches please let me know.

Why do I want to fit this data? Firstly, I need some kind of look-up for various x-values which might not coincide with measured x-values. Secondly, I need to get rid of the scatter in the end of the measurement for further processing. Is there perhaps a simpler way to achieve this?

Code for reference w/o attachment:

E = dlmread('data.txt');
x = E(:,1);
y = E(:,2);
q = [1; .25; .25];
function res = f(x,q)
res = q(1) - exp((q(2).*x).^q(3));
end
[fr,q,cvg,iter_r] = leasqr(x,y,q,'f',.0001,40);

Any help would be appreciated. Thanks and kind regards, Jan

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The data file that you attached is faulty.

try plotting just the x values

plot(x)

DAS

From:	Tweety
Subject:	Re: Step-function fit using leasqr
Date:	Fri, 2 Sep 2016 09:18:25 +0200
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