Model selection
Bootstrap methods in computer simulation experiments
WSC '95 Proceedings of the 27th conference on Winter simulation
On batch means in the simulation and statistics communities
WSC '95 Proceedings of the 27th conference on Winter simulation
The threshold bootstrap: a new approach to simulation output analysis
WSC '93 Proceedings of the 25th conference on Winter simulation
Uniform and bootstrap resampling of empirical distributions
WSC '93 Proceedings of the 25th conference on Winter simulation
Validation of Trace-Driven Simulation Models: a Novel Regression Test
Management Science
Bootstrapping and validation of metamodels in simulation
Proceedings of the 30th conference on Winter simulation
Validation of models: statistical techniques and data availability
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
VV&A; IV: validation of trace-driven simulation models: more on bootstrap tests
Proceedings of the 32nd conference on Winter simulation
VV&A; IV: validation of trace-driven simulation models: more on bootstrap tests
Proceedings of the 32nd conference on Winter simulation
Proceedings of the 32nd conference on Winter simulation
Resampling methods for input modeling
Proceedings of the 33nd conference on Winter simulation
Proceedings of the 2011 ACM Symposium on Applied Computing
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'Trace-driven' or 'correlated inspection' simulation means that the simulated and the real systems have some common inputs (say, arrival times) so the two systems' outputs are cross-correlated. To validate such simulation models, this paper formulates six validation statistics, which are inspired by practice and statistical analysis; for example, the simplest statistic is the difference between the average simulated and real responses. To evaluate these validation statistics, the paper develops novel types of bootstrapping based on subruns. Three basic bootstrap procedures are devised, depending on the number of simulation replicates: one, two, or more replicates. Moreover, for the case of more than two replicates the paper considers conditional versus unconditional resampling. These six validation statistics and four bootstrap procedures are evaluated in extensive Monte Carlo experiments with single-server queueing systems. The main conclusion is that bootstrapping of the simplest validation statistic gives the correct type I error probability, and has relatively high power.