numhessian(f, {args}, minarg) Numeric second derivative of f with respect to argument "minarg". * first argument: function name (string) * second argument: all arguments of the function (cell array) * third argument: (optional) the argument to differentiate w.r.t. (scalar, default=1) If the argument is a k-vector, the Hessian will be a kxk matrix function a = f(x, y) a = x'*x + log(y); endfunction numhessian("f", {ones(2,1), 1}) ans = 2.0000e+00 -7.4507e-09 -7.4507e-09 2.0000e+00 Now, w.r.t. second argument: numhessian("f", {ones(2,1), 1}, 2) ans = -1.0000
Package: optim