A function's robustness is determined by the component with the worst asymptotic growth rate

This is very like the Big-O notation in a sense that the worst component dominates, while others go invisible. Instead of computing performance, we compute the robustness against extreme values. The influence function measures the impact of a single observation on the function’s output as the observation grows extreme.