Regression line that includes x and y errors.

2023 2 20
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更新时间：2023 2 20
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Hi,
I have x and y data set, and each x and y variables have 5% and 10% uncertainty or error, respectively. How I should find a one regresion or best fit line (Best_y = mx + c) for such a dataset? Here is the dataset. Any thoughts? Thanks.

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Matt J
Matt J 2023-2-20
编辑：Matt J 2023-2-20

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I would recommend linear2dFit() form this FEX download,
https://www.mathworks.com/matlabcentral/fileexchange/87584-object-oriented-tools-for-fitting-conics-and-quadrics
fitResult=linear2dFit([x,y]')

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Research
Research 2023-2-20
Thanks. I tried to run the example code, but got error on this line: xy=linear2dFit.xysim(p1, p2, t, sig). The error is The specified superclass 'conicFit' contains a parse error, cannot be found on MATLAB's search path, or is shadowed by another file with the same name.
I found that I dont have "linear2dFit.xysim" FEX function. I'm missing anything. Thanks.
Matt J
Matt J 2023-2-20
It sounds to me like you only downloaded linear2dFit. You need to download all the files.
Research
Research 2023-2-20
Thanks. It runs now. This is a great function. So, just I understand the linear2dFit function, particularly how the function incorporates the error values. In my case, I need to build an array (xy here) that includes +/-x and +/-y error values.This xy array has x and y values also error dx and dy values too. I believe the function then find a best fit through all these points. Thanks!
Matt J
Matt J 2023-2-20
编辑：Matt J 2023-2-20
Thanks. It runs now. This is a great function
Glad it's working for you, but if it's doing what you need, I'd be much obliged if you'd Accept-click the answer.
particularly how the function incorporates the error values?
The fit is a total least squares fit, so it assumes there are errors in both x and y.

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