Re: Weighted polyfit?

[Matthias Brennwald]

On Mar 26, 2010, at 2:42 PM, Ben Abbott wrote:

> 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

Oh, thanks!