Statistical tools for simulation practitioners
Statistical tools for simulation practitioners
State-of-the-Art Review: A User's Guide to the Brave New World of Designing Simulation Experiments
INFORMS Journal on Computing
Game-theoretic validation and analysis of air combat simulation models
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on model-based diagnostics
Proceedings of the Winter Simulation Conference
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This paper focuses on simulation output that may be censored; that is, the output has a limited range (examples are simulations that have as output the time to occurrence of a specific event - such as a 'rare' event - within a fixed time horizon). For sensitivity analysis of such simulations we discuss three alternatives: (i) traditional polynomial regression models, (ii) logistic or logit regression, and (iii) tobit analysis. The case study concerns the control of a specific animal disease (namely, IBR) in The Netherlands. The simulation experiment has 31 environmental factors or inputs, combined into 64 scenarios - each replicated twice. Traditional polynomial regression gives some estimated main effects with wrong signs. Logit regression correctly predicts whether simulation output is censored or not, for 92% of the scenarios. Tobit analysis does not give effects with wrong signs; it correctly predicts censoring, for 89% of the scenarios.