Using sectioning to construct confidence intervals for quantités when applying antithetic variates

Research output: Contribution to journalConference articlepeer-review


We use sectioning to construct a confidence interval (CI) for a quantile when applying antithetic variates, which is a well-known variance-reduction technique. Closely related to batching, sectioning starts with the batching CI and replaces the batching quantile estimator with the overall quantile estimator throughout. Since the overall quantile estimator often has smaller bias than the batching quantile estimator, the sectioning CI is centered at a better point estimator, and this should lead to sectioning CIs having better coverage than batching CIs.

Original languageEnglish (US)
Pages (from-to)172-179
Number of pages8
JournalSimulation Series
Issue number10
StatePublished - 2014
EventSummer Computer Simulation Conference, SCSC 2014, Part of the 2014 Summer Simulation Multiconference, SummerSim 2014 - Monterey, United States
Duration: Jul 6 2014Jul 10 2014

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications


  • Antithetic variates
  • Confidence interval
  • Monte Carlo
  • Quantile
  • Sectioning
  • Value-at-risk
  • Variance reduction

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