Hi Korhan,
I understand that you are working on fitting your model to your data. As you correctly mentioned, the error you're encountering is due to the residuals falling below the tolerance limits. One possible solution is to increase the tolerance by adjusting the "TolFun" parameter. However, I understand that you prefer not to do that. Based on the information you've provided, here are a few options you can consider:
- Data characteristics: Noisy data can slow down the convergence of the model or prevent it from converging at all. Be sure to thoroughly check the data for any inconsistencies or noise.
- Choice of model: The model you have selected might have inherent limitations that hinder its convergence. Consider exploring alternative models that may provide a better fit to your data.
- Initial parameters: The initial parameter values you provide to the model can significantly impact the convergence speed. If the initial parameters are far from the optimal solution, the fitting process may be slower. Ensuring that your initial parameter estimates are closer to the expected values can help improve convergence.
To provide more specific help, please share additional details about the data and the specific model you are working with.
For more information about the “fit” function, refer to the below documentation:
I hope it helps.
