Nonlinear fit to data with errors in both coordinates
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Hi
I have a set of data (x, y), where there are measurement errors on both coordinates. These errors are non-constant, and I wish to fit a nonlinear function to the data.
By using nlinfit I am able to fit my function to the data including the errors on y. But is there a way for me to include the ones in x as well?
I would be very happy to get a push in the right direction. I couldn't seem ti find an answer using the "search".
Thanks in advance.
Niles.
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Star Strider
2012-9-21
This is known as a Total Least Squares problem. There appear to be a number of File Exchange contributions on the Total Least Squares Method, but I haven't looked at them to see if any apply to nonlinear least squares. I imagine that the same techniques would apply, although I have never had occasion to use it in a nonlinear regression context.
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