This came up as I was reading about Non-linear least squares fitting.
We have data points .
We wish to find the vector of parameters that gives the best fit in the least squares sense.
So we have our model function .
Now we define the residual function by .
Then we wish to minimize the function .
Here is my question, how would I get the gradient of this function?
The book says , where J denotes the Jacobian.
I donīt really follow..