Bayesian estimation for the M/G/1 queue using a phase-type approximation

dc.contributor.author	Ausín, M. Concepción
dc.contributor.author	Wiper, Michael P.
dc.contributor.author	Lillo, Rosa E.
dc.date.accessioned	2007-07-05T14:58:28Z
dc.date.available	2007-07-05T14:58:28Z
dc.date.issued	2004
dc.identifier.citation	Journal of Statistical Planning and Inference, 2004, 118, p. 83 – 101	es_ES
dc.identifier.issn	0378-3758
dc.identifier.uri	http://hdl.handle.net/2183/866
dc.description.abstract	This 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.	es_ES
dc.format.mimetype	application/pdf
dc.language.iso	eng	es_ES
dc.publisher	Elsevier	es_ES
dc.relation.uri	http://www.elsevier.com	es_ES
dc.subject	Queues	es_ES
dc.subject	Bayesian mixtures	es_ES
dc.subject	Reversible jump MCMC	es_ES
dc.subject	Phase-type distributions	es_ES
dc.subject	Matrix geometric methods	es_ES
dc.title	Bayesian estimation for the M/G/1 queue using a phase-type approximation	es_ES
dc.type	info:eu-repo/semantics/article	es_ES
dc.rights.access	info:eu-repo/semantics/openAccess	es_ES