A guide to simulation (2nd ed.)
A guide to simulation (2nd ed.)
Some Modest Proposals for Simulation Software: Design and Analysis of Experiments
SS '01 Proceedings of the 34th Annual Simulation Symposium (SS01)
Representing and generating uncertainty effectively
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Introduction to modeling and generating probabilistic input processes for simulation
Proceedings of the 40th Conference on Winter Simulation
A tutorial on simulation modeling in six dimensions
Proceedings of the Winter Simulation Conference
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Stochastic simulations involve random inputs, so produce random outputs too. This introductory tutorial is meant to call attention to the need to model and generate such inputs in ways that may not be the standard or defaults in simulation-modeling software, yet can be critical to model validity (a.k.a. getting right rather than wrong answers). There are both dangers involved with doing this inappropriately, as well as opportunities to do things better, making for more accurate and more precise results from simulations. Specific issues include possible dependence across and within random inputs, use of empirical distributions even if a "standard" fits the data, and non-default use of the underlying random-number generator. Suggestions for novel ways of implementing some of these ideas in simulation-modeling software are offered.