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Confusing about applying weighted least square for constant fitting

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WeiHao Xu
WeiHao Xu on 19 Jul 2021
Commented: Matt J on 19 Jul 2021
I'm now fitting a line with noise. My equation is to minimize corresponding to equation , then I have and with data. I want to caculate the best y. The WSL gives for the answer. But now my confusing is what is Y? Is this , which means my code is
(1) is the matrix with number 1. Is this right for me? or I should use other function such as fminsearch(I saw in the community, maybe it's still my missunderstanding)...Thanks

Accepted Answer

Matt J
Matt J on 19 Jul 2021
Edited: Matt J on 19 Jul 2021
I would recommend lscov
p=lscov(x(:).^[1,0],y,w/N);
yfit=polyval(p,x)
  6 Comments
Matt J
Matt J on 19 Jul 2021
You're welcome, but if you find that one of the answers does what you want, please do Accept-click it.

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More Answers (1)

Torsten
Torsten on 19 Jul 2021
Edited: Torsten on 19 Jul 2021
X = ones(N,1)
W = diag(w)
Y = y
where y is the (Nx1) column vector of the measurements and w is the (Nx1) column vector of weights.
The result of your formula is the coefficient a of the line y=a that best approximates the measurements.
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