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Output Analysis - OutputAnalysis TheresaM.Roeder Spring2011...

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Output Analysis Theresa M. Roeder Spring 2011
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Simulation Output Analysis Ø Perspectives and issues Ø Serial correlation Ø Interval estimation Ø Non-parametric methods Ø (Multiple responses)
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Perspectives Stages of Study 1. Modeling and validation 2. System evaluations (high-level) 3. System design (details) 4. Implementation P r i m a r y O u t p u t Main Questions: Where and when to spend study resources?
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Animations Ø Have been mostly physical (not logical) Ø Have made simulations more popular + System interactions + Verification and validation + Training and shop floor credibility + Logic development and testing - Take valuable study resources to develop and maintain - Serve no analytical purpose, maybe negative value - Force a particular framework or “world-view”
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Validation: Turing Test Ø Hypothesis: A manager familiar with the real system cannot tell the difference between outputs of the simulation and the outputs of the real system Ø Basic Approach: Give the manager both simulation output and output of the real system and see if (s)he can tell the difference Ø Advantages: If manager cannot tell difference, confidence in model established. If can tell difference, can point out why simulation results are different and the model can be changed to better reflect real system.
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Statistics We want: Ø Good estimator High accuracy (low bias) Good precision (low variance) General validity (robustness) Meaningful insights (interpretations)
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Statistics Ø Measurement of Estimator Goodness Sources and effect of bias Interval estimates confidence intervals prediction intervals tolerance intervals etc. etc. etc.
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