Calculating error in coefficients determined from fitting a curve to data?

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SUMMARY

The discussion focuses on calculating the error associated with coefficients derived from fitting a curve to data points modeled by the function y = a exp(-b ln²(c/x)). The coefficients a, b, and c are determined from the data, and the user seeks to quantify the uncertainty in these coefficients using the residuals from the fitting process. A proposed method involves utilizing the partial derivatives of the coefficients with respect to the data points and summing the contributions of the associated errors.

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  • Knowledge of partial derivatives in multivariable calculus
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I have a set of data points (x0, y0), (x1, y1), ... (xi, yi)

With each yi there is an associated error ei.

The data is modeled by the function:

[tex]y = a\exp(-bln^2(c/x))[/tex]

I have determined values for the coefficients a, b, c and I know the residuals produced from the values of the coefficients I've calculated and the set of data. What I'm trying to do now is to calculate the error, or uncertainty if you prefer, associated with each coefficient. How do I go about this?
 
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A rough approach could be this one:

if you calculated the coefficients a, b, and c starting from your data, it means you have at your disposal a formula for theese coefficients. For example

[itex]a = a (x_1,\dots,x_n,y_1,\dots,y_n)[/itex]

Then you could write

[itex]\Delta a = \sum_{k=1}^n\frac{\partial a}{\partial y_k}\epsilon_k[/itex]
 

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