Nonlinear fit to data with errors in both coordinates

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.

[Star Strider]

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.

[Niles Martinsen]

Thanks, I will definately check it out. It's kind of you to help me so often.

Best, Niles.