Turing a Least Squares function into a Weighted Least Squares

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Ben 2012-10-26

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https://ww2.mathworks.cn/matlabcentral/answers/51987-turing-a-least-squares-function-into-a-weighted-least-squares

So i originally wrote my function for a least squared function but it turns out I need to write my function to figure out the weighted least squares. From my understanding, a weighted least squares problem can be solved by the basic least squares method after we multiply both Yi and the ith row of X by wi in a typical equation. But how do I should this in a matlab function?

function [A, e] = WeightedLeastSquares(X, Y, w) size(A) rank(A) rank([A b]) X = A\b Y = norm(A*X) w = pinv(A)*b

I already have the variables A,e, X,Y,w loaded onto my current workspace, but I just need to change my function. So, if I call,

load Lab08Data.mat
I get
[A, e] = WeightedLeastSquares(X3, Y3, w)
A =
3.0573
1.9250
e =
0.0218
-0.0702
0.3235
0.0552
-0.1038
-0.0202

Any suggestions on how turn my function to a weighted least squares function?

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Ben 2012-10-26

you just have to use polyfit and it should work!

SB 2012-10-26

I dont think we're allowed to use polyfit; it defeats the purpose of the problem.

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