Estimating Customer and Time Averages

Peter W. Glynn, Benjamin Melamed and Ward Whitt
Additional contact information
Peter W. Glynn: Stanford University, Stanford, California
Benjamin Melamed: NEC Research USA, Inc., Princeton, New Jersey
Ward Whitt: AT&T Bell Laboratories, Murray Hill, New Jersey

Operations Research, 1993, vol. 41, issue 2, 400-408

Abstract: In this paper we establish a joint central limit theorem for customer and time averages by applying a martingale central limit theorem in a Markov framework. The limiting values of the two averages appear in the translation terms. This central limit theorem helps to construct confidence intervals for estimators and perform statistical tests. It thus helps determine which finite average is a more asymptotically efficient estimator of its limit. As a basis for testing for PASTA (Poisson arrivals see time averages), we determine the variance constant associated with the central limit theorem for the difference between the two averages when PASTA holds.

Keywords: queues; limit theorems: central limit theorems for customer and time averages; queues; statistical inference: estimating customer and time averages; statistics; estimation: averages over time and at embedded points (search for similar items in EconPapers)
Date: 1993
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://dx.doi.org/10.1287/opre.41.2.400 (application/pdf)

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:inm:oropre:v:41:y:1993:i:2:p:400-408

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().