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This is my first post and I'm not sure if this is the right forum. Please redirect if necessary.

I'm new to nonlinear regression, but from what I've read I realize that making "good" initial guesses for the model parameters is very important, otherwise a "best fit" may not result.

I'm using an analytical instrument where the user selects from a short list of mathematical models (please see attachments), a calibration is performed, and the model parameters are calculated. There is no other user input.

This implies, and it is stated in the Operator's Manual, that the initial guesses are calculated using a noniterative algorithm in conjunction with the calibration data.

I would love for someone to show me how to derive theses algorithms for the models attached.

If there is any other information that is required in my quest please let me know. I can supply actual data if necessary.

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# Non Linear Regression Initial Guesses

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