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Weighted Least squares fitting
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I want to fit a specific function to a set of data x, y with errors sx and sy respectively. I know how to fit the function using curve_fit from scipy.optimize but I dont know how to account for the errors in both x and y.
I also want to calculate the chi squared value to determine the goodness of the fit.
How will I do that?
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