In this lecture, we review estimating absolute performance from simulation, with focus on choosing the number of necessary replications of transient simulations of terminating systems. The lecture starts by overviewing point estimation, bias, and different types of point estimators. This includes an overview of quantile estimation and how to use quantile estimation to use simulations as null-hypothesis-prediction generators. We the introduce interval estimation with confidence intervals and prediction intervals. Confidence intervals, which are visualizations of t-tests, provide an alternative way to choose the number of required replications without doing a formal power analysis.
Archived lectures from undergraduate course on stochastic simulation given at Arizona State University by Ted Pavlic
Friday, November 4, 2022
Lecture J2 (2022-11-03): Estimation of Absolute Performance, Part II (Terminating Systems/Transient Simulations)
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