Bayesian estimation for the M/G/1 queue using a phase-type approximation
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Bayesian estimation for the M/G/1 queue using a phase-type approximationFecha
2004Cita bibliográfica
Journal of Statistical Planning and Inference, 2004, 118, p. 83 – 101
Resumen
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.
Palabras clave
Queues
Bayesian mixtures
Reversible jump MCMC
Phase-type distributions
Matrix geometric methods
Bayesian mixtures
Reversible jump MCMC
Phase-type distributions
Matrix geometric methods
Versión del editor
ISSN
0378-3758