10.4230/OASICS.SCOR.2012.21
Blair, Shona
Shona
Blair
Bedford, Tim
Tim
Bedford
Quigley, John
John
Quigley
Empirical Bayes Methods for Discrete Event Simulation Performance Measure Estimation
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
2012
Article
Discrete Event Simulation
Analysis Methodology
Empirical Bayes
Ravizza, Stefan
Stefan
Ravizza
Holborn, Penny
Penny
Holborn
2012
2012-06-26
2012-06-26
2012-06-26
en
urn:nbn:de:0030-drops-35436
10.4230/OASIcs.SCOR.2012
978-3-939897-39-2
2190-6807
10.4230/OASIcs.SCOR.2012
OASIcs, Volume 22, SCOR 2012
3rd Student Conference on Operational Research
2012
22
3
21
30
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Ravizza, Stefan
Stefan
Ravizza
Holborn, Penny
Penny
Holborn
2190-6807
Open Access Series in Informatics (OASIcs)
2012
22
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
10 pages
411076 bytes
application/pdf
Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license
info:eu-repo/semantics/openAccess
Discrete event simulation (DES) is a widely-used operational research methodology facilitating the analysis of complex real-world systems. Although, generally speaking, simplicity is greatly desirable in DES modelling applications, in many cases the nature of the underlying system results in simulation models which are large in scale, complex, and expensive to run. As such, the careful design and analysis of simulation experiments is essential to ensure valid and efficient inference concerning DES model performance measures. It is envisaged that empirical Bayes (EB) methods, which enable data to be pooled across a set of populations to support inference of the parameters of a single population, may be of use within this context. Despite this potential, EB has so far been neglected within the DES literature. This paper presents a preliminary computational investigation into the efficacy of EB procedures in the estimation of DES performance measures. The results of this investigation, and their significance, are explored. Additionally, likely directions for future research are also addressed.
OASIcs, Vol. 22, 3rd Student Conference on Operational Research, pages 21-30