Abstract
In this paper, by considering an M|M|1|∞ queueing model, Bayes estimators of traffic intensity and measures of system performance are worked out under squared error loss function (SELF) based on observed data on the independent interarrival and service times. Further, minimum posterior risk associated with Bayes estimators of traffic intensity and system performance measures are obtained under SELF. Numerical illustration of the performance of the estimates is given through simulation study. It is shown that Bayes estimators perform better than the maximum likelihood estimators under the influence of prior information.
Highlights
Since the arrival time and service time of entities in the queue are stochastic, it will be of interest to carry out inferential procedures to study and analyze the behaviour of the parameters of the queueing models by assuming suitable probability distributions
The rest of the paper is organized as follows: In Section 2, we introduce the model and describe the inferential aspects including Bayes estimators of the parameters and measures of system performance under squared error loss function (SELF)
An attempt is made in this paper to study the Bayesian estimation of M |M |1|∞ queueing model when sample observations are available on independent interarrival and service times of entities at some points of times
Summary
Queueing models are often used in the design and analysis of telecommunication systems, traffic systems, service systems and so on. Since the arrival time and service time of entities in the queue are stochastic, it will be of interest to carry out inferential procedures to study and analyze the behaviour of the parameters of the queueing models by assuming suitable probability distributions. This can be done either through the frequentist or Bayesian approach.
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