International Journal of Applied Research
Vol. 2, Issue 2, Part L (2016)
Bayesian analysis for the m/g/n queue using a phase type approximation
In this paper we study with Bayesian implication and forecasting for M/G/n queueing systems. The general service time density is approximated with a class of Erlang mixtures which are phase type distributions. Specified this phase type approximation, an explicit assessment 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.
How to cite this article:
Yogesh Shukla, RK Shrivastava. Bayesian analysis for the m/g/n queue using a phase type approximation. Int J Appl Res 2016;2(2):731-733.