Forecast Uncertainty and Monte Carlo Simulation

Sam Sugiyama has written a primer on the use of Monte Carlo Simulation to assess forecast error. His simple illustrative example and description of the steps in the MCS procedure provide a non-technical overview of this fascinating approach to the evaluation of uncertainty in forecasts. For regression modelers specifically, Sam shows how MCS can be used to develop more realistic prediction intervals than the theoretical PIs found in books and software. Copyright International Institute of Forecasters, 2007