Robust Monte Carlo Simulation

Robust Monte Carlo simulation extends standard Monte Carlo by explicitly accounting for uncertainty in input distributions, model structure, or parameter assumptions. Rather than assuming a single fixed probability distribution for each input, the analyst considers a family of plausible distributions and evaluates how sensitive the output is to those choices, yielding conclusions that hold across a range of reasonable assumptions.