Hi all. I was thinking on how we can maximize a function with the following form: F(y, x1, x2,..., xn) with y=f(x1) I know that I should use the total derivative to find out the effective rate of y, but I don't see how gradient and Hessian should be organized in this context. For example, if we have F(y, x1, x2) with y=f(x1), how should we set gradient and Hessian? Should the gradient be [itex]\nabla[/itex]F= (F1, F2)? Or [itex]\nabla[/itex]F= (Fy, F1, F2) What about the Hessian? Sorry for the question (maybe not exactly challenging...), but this problem is not explicitly mentioned in any book. Thanks.