The choice is between nlinfit and lsqcurvefit, depending on what you want to do. The Statistics Toolbox nlinfit provides myriad statistics if you want them, but will only fit vector dependent variables. The Optimization Toolbox lsqcurvefit can fit matrix dependent variables, but doesn’t have all the statistics options. (Both can take matrix independent variables, but that requires you deceive the fitting function into believing it has a vector independent variable in your objective function programming. That’s not difficult. The fitting functions are credulous.)
So, if you’re fitting vector dependent variables, go for nlinfit. If you’re fitting matrix dependent variables, go for lsqcurvefit.
My opinion. Others may differ.
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