Paper Info
Title
Bayesian prediction of the transient behaviour and busy period in short- and long-tailed GI/G/1 queueing systems
Abstract
Bayesian inference for the transient behaviour and duration of a busy period in a single server queueing system with general, unknown distributions for the interarrival and service times is investigated. Both the interarrival and service time distributions are approximated using the dense family of Coxian distributions. A suitable reparameterization allows the definition of a non-informative prior, and Bayesian inference is then undertaken using reversible jump Markov chain Monte Carlo methods. An advantage of the proposed procedure is that heavy-tailed interarrival and service time distributions such as the Pareto can be well approximated. The proposed procedure for estimating the system measures is based on recent theoretical results for the Coxian/Coxian/1 system. A numerical technique is developed for every MCMC iteration so that the transient queue length and waiting time distributions and the duration of a busy period can be estimated. The approach is illustrated with both simulated and real data.
Year
DOI
Venue
2008
10.1016/j.csda.2007.05.009
Computational Statistics & Data Analysis
Keywords
DocType
Volume
bayesian inference,coxian distribution,heavy tails,queueing systems,semiparametric modelling,transient analysis,reversible jump.
Journal
52
Issue
ISSN
Citations 
3
Computational Statistics and Data Analysis
2
PageRank 
References 
Authors
0.49
11
2
Name
Order
Citations
PageRank
M. Concepcion120.49
Aus ¶ ‡220.49