4 Functions for numerical approximation of gradients and Hessians

You should not usually need to use these functions directly or pass them as arguments. They should be chosen and used by optimizer functions, possibly subject to their configuration options.

• dfpdp: Direct user interface to default numerical gradient method of new frontends.
• deriv: Higher order numerical derivatives.
• numgradient: Another numerical gradient function.
• numhessian: Numerical Hessian function.
• cdiff: A string, yielding the numerical gradient if evaluated.
• jacobs: Complex step derivatives.