Mathematica Curve Fitting With Uncertainties

AI Thread Summary
The discussion focuses on fitting a nonlinear model to data points that include uncertainties in both x and y values. While the Weights command in Mathematica can handle uncertainties in y values, the challenge remains in incorporating uncertainties in x values. The concept of "errors in variables" is highlighted as a potential solution for this issue. Participants are encouraged to explore resources on this topic for further guidance. Understanding how to effectively include both types of uncertainties is crucial for accurate curve fitting.
Screwdriver
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I have a set of data points \{\{x_1, y_1\}, \{x_2, y_2\} ... \} each with an uncertainty \{\{dx_1, dy_1,\}, \{dx_2, dy_2\} ...\}. Is there any way of fitting a nonlinear model to the data that incorporates the uncertainties on both x and y? I know that you can use the Weights command to incorporate the uncertainties on the y values, but I don't know how to get the x uncertainties in there as well.
 
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Screwdriver said:
I have a set of data points \{\{x_1, y_1\}, \{x_2, y_2\} ... \} each with an uncertainty \{\{dx_1, dy_1,\}, \{dx_2, dy_2\} ...\}. Is there any way of fitting a nonlinear model to the data that incorporates the uncertainties on both x and y? I know that you can use the Weights command to incorporate the uncertainties on the y values, but I don't know how to get the x uncertainties in there as well.

You need to read up on "errors in variables":

http://www.wavemetrics.com/products/igorpro/dataanalysis/curvefitting/errorsinvariables.htm
 
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