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Re: Weighted polyfit?
From: |
Ben Abbott |
Subject: |
Re: Weighted polyfit? |
Date: |
Fri, 26 Mar 2010 09:42:16 -0400 |
On Mar 26, 2010, at 5:36 AM, Matthias Brennwald wrote:
> Dear all
>
> I am pretty sure this is something that has been discussed previously, but I
> was not able to find anything helpful. I'd like to fit a polynomial to my
> experimental data. The data have errors, and I'd like to use these errors as
> weights for the data values in the fit. Something like this:
>
> x = [0:10]; % x values of experimental data
> y = x.^2; % y values of experimental data
> y_err = randn(size(x)); % errors of y
> [p,s] = polyfit (x,y,2); % <-- replace this by something that
> takes into account the errors (y_err), e.g. using the weights 1./y_err for
> each value in y
>
> Any hints or ideas?
>
> Matthias
Have you looked at wpolyfit.m from the optim package?
http://octave.sourceforge.net/optim/function/wpolyfit.html
Ben