Numerical Recipes in C++: the art of scientific computing
Numerical Recipes in C++: the art of scientific computing
Simulation Modeling and Analysis
Simulation Modeling and Analysis
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Using Ranking and Selection to "Clean Up" after Simulation Optimization
Operations Research
Computational Statistics & Data Analysis
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The validation of dependability or performance requirements is often done experimentally using simulation experiments. In several applications, the experiments have a binary output which describes whether a requirement is met or not. In highly dependable systems the probability of missing a requirement is 10−6 or below which implies that statistically significant results have to be computed for binomial distributions with a small probability. In this paper we compare different methods to statistically evaluate simulation experiments with highly dependable systems. Some of the available methods are extended slightly to handle small probabilities and large samples sizes. Different problems like the computation of one or two sided confidence intervals, the comparison of different systems and the ranking of systems are considered.