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Weighted polyfit?
From: |
Matthias Brennwald |
Subject: |
Weighted polyfit? |
Date: |
Fri, 26 Mar 2010 10:36:08 +0100 |
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
- Weighted polyfit?,
Matthias Brennwald <=