Analyzing Simulation Experiments with Common Random Numbers

Jack Kleijnen ()

Management Science, 1988, vol. 34, issue 1, 65-74

Abstract: To analyze simulation runs which use the same random numbers, the blocking concept of experimental design is not needed. Instead, this paper applies a linear regression model with a nondiagonal covariance matrix. This covariance matrix does not need to have a specific pattern such as constant covariances. A simple example yields surprising results. The paper proposes a new framework for the error analysis. This framework consists of three factors (namely, common random numbers, replication, model validity), each with three levels.

Keywords: blocking; variance reduction; estimated generalized least squares; general linear model; error analysis (search for similar items in EconPapers)
Date: 1988
References: Add references at CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.34.1.65 (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:ormnsc:v:34:y:1988:i:1:p:65-74

Access Statistics for this article

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