A guide to simulation (2nd ed.)
A guide to simulation (2nd ed.)
Regeneration and networks of queues
Regeneration and networks of queues
Likelihood ratio gradient estimation for stochastic systems
Communications of the ACM - Special issue on simulation
Bias properties of budget constrained simulations
Operations Research
Notes: conditions for the applicability of the regenerative method
Management Science
Optimal mean-squared-error batch sizes
Management Science
Can the regenerative method be applied to discrete-event simulation?
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Derandomizing Variance Estimators
Operations Research
Empirical performance of bias-reducing estimators for regenerative steady-state simulations
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Logic and stochastic modeling with SMART
Performance Evaluation - Modelling techniques and tools for computer performance evaluation
The semi-regenerative method of simulation output analysis
ACM Transactions on Modeling and Computer Simulation (TOMACS)
On the theoretical comparison of low-bias steady-state estimators
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Non-linear control variates for regenerative steady-state simulation
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Nonexistence of a class of variate generation schemes
Operations Research Letters
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The regenerative method possesses certain asymptotic properties that dominate those of other steady-state simulation output analysis methods, such as batch means. Therefore, applying the regenerative method to steady-state discrete-event system simulations is of great interest. In this paper, we survey the state of the art in this area. The main difficulty in applying the regenerative method in our context is perhaps in identifying regenerative cycle boundaries. We examine this issue through the use of the "smoothness index." Regenerative cycles are easily identified in systems with unit smoothness index, but this is typically not the case for systems with nonunit smoothness index. We show that "most" (in a certain precise sense) discrete-event simulations will have nonunit smoothness index, and extend the asymptotic theory of regenerative simulation estimators to this context.