Perhaps least_squares is what you're looking for? Yes, I agree on that. On Wed, at 20:08, JayNerella wrote: curve_fit is when you have a set of measured data, a function that describes the data, and a set of parameters to optimise (that minimises the least squares difference between the function and the data).
If you want to introduce the independent variables to least_squares you need to use the args keyword. In your example xdata and ydata are the independent variables, and z is a synthesised dependent variable.
Sorry, I can't help with matlab related questions, I've never used it. = matlab I am getting resnorm of 5.2769e+35 which is very high. I have solve the same problem in matlab using the following code:Ĭ1 = x(3) (xdata - ydata) - x(2)(-xdata)
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