A guide to simulation (2nd ed.)
A guide to simulation (2nd ed.)
Operations Research
Nonparametric techniques in simulation analysis: a tutorial
WSC '94 Proceedings of the 26th conference on Winter simulation
WSC '94 Proceedings of the 26th 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
A parametric version of jackknife-after-bootstrap
Proceedings of the 30th conference on Winter simulation
Bootstrapping and validation of metamodels in simulation
Proceedings of the 30th conference on Winter simulation
Bootstrap confidence intervals for ratios of expectations
ACM Transactions on Modeling and Computer Simulation (TOMACS)
VV&A; IV: validation of trace-driven simulation models: more on bootstrap tests
Proceedings of the 32nd conference on Winter simulation
Analysis of simulation experiments by bootstrap resampling
Proceedings of the 33nd conference on Winter simulation
IEEE Transactions on Software Engineering
Statistical Characterization of Protein Ensembles
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Issues in the implementation of software process improvement project in Malaysia
WSEAS Transactions on Information Science and Applications
Investigation of domain effects on software
Proceedings of the 47th Annual Southeast Regional Conference
Input uncertainty in outout analysis
Proceedings of the Winter Simulation Conference
Agent based simulation output analysis
Proceedings of the Winter Simulation Conference
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We critically review the work that has been done in applying basic, smoothed and parametric bootstrap methods to simulation experiments. We develop a framework to classify bootstrap methods in this context and use it to compare various bootstrap schemes. Most bootstrap methods are hard to analyse theoretically. An exception is the parametric case for which a detailed analysis can be carried out. An interesting result in this case is that, whereas in standard statistical experiments bootstrap samples give only information about the variance of a statistic and not its mean, this turns out not to be so in simulation experiments. Thus parametric bootstrap samples can be advantageously included in estimates of the responses of interest.