Ausín, M. ConcepciónWiper, Michael P.Lillo, Rosa E.2007-07-052007-07-052004Journal of Statistical Planning and Inference, 2004, 118, p. 83 – 1010378-3758http://hdl.handle.net/2183/866This article deals with Bayesian inference and prediction for M/G/1 queueing systems. The general service time density is approximated with a class of Erlang mixtures which are phase-type distributions. Given this phase-type approximation, an explicit evaluation of measures such as the stationary queue size, waiting time and busy period distributions can be obtained. Given arrival and service data, a Bayesian procedure based on reversible jump Markov Chain Monte Carlo methods is proposed to estimate system parameters and predictive distributions.application/pdfengQueuesBayesian mixturesReversible jump MCMCPhase-type distributionsMatrix geometric methodsjournal articleopen access