The semi-regenerative method of simulation output analysis

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We develop a class of techniques for analyzing the output of simulations of a semi-regenerative process. Called the semi-regenerative method, the approach is a generalization of the regenerative method, and it can increase efficiency. We consider the estimation of various performance measures, including steady-state means, expected cumulative reward until hitting a set of states, derivatives of steady-state means, and time-average variance constants. We also discuss importance sampling and a bias-reduction technique. In each case, we develop two estimators: one based on a simulation of a single sample path, and the other a type of stratified estimator in which trajectories are generated in an independent and identically distributed manner. We establish a central limit theorem for each estimator so confidence intervals can be constructed.

Original languageEnglish (US)
Pages (from-to)280-315
Number of pages36
JournalACM Transactions on Modeling and Computer Simulation
Issue number3
StatePublished - 2006

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Computer Science Applications


  • Bias reduction
  • Efficiency improvement
  • Importance sampling
  • Regenerative processes
  • Variance reduction


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