We need thus to compute the inverse of the Jacobian matrix and it is to understand that difficulties may arise in case \( \hat{J} \) is nearly singular.
It is rather straightforward to extend the above scheme to systems of more than two non-linear equations. In our case, the Jacobian matrix is given by the Hessian that represents the second derivative of cost function.