Confidence intervals in discrete event simulation: A comparison of replication and batch means

Averill M. Law

Naval Research Logistics Quarterly, 1977, vol. 24, issue 4, 667-678

Abstract: Suppose that we have enough computer time to make n observations of a stochastic process by means of simulation and would like to construct a confidence interval for the steady‐state mean. We can make k independent runs of m observations each (n=k.m) or, alternatively, one run of n observations which we then divide into k batches of length m. These methods are known as replication and batch means, respectively. In this paper, using the probability of coverage and the half length of a confidence interval as criteria for comparison, we empirically show that batch means is superior to replication, but that neither method works well if n is too small. We also show that if m is chosen too small for replication, then the coverage may decrease dramatically as the total sample size n is increased.

Date: 1977
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1002/nav.3800240414

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:navlog:v:24:y:1977:i:4:p:667-678

Access Statistics for this article

More articles in Naval Research Logistics Quarterly from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().