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In this paper, by considering an M|M|1|1 queueing model, Bayesian estimation of traffic intensity and measures of system performance are worked out under the squared error loss function (SELF) based on the observed data on 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 informations. [ABSTRACT FROM AUTHOR]

By considering an M | D | 1 queueing system, the maximum likelihood and consistent estimators of traffic intensity are derived by observing the number of entity arrivals during the service time of an entity. Uniform minimum variance unbiased estimators for the expected waiting times per entity in the system and queue are obtained. Further, Bayes estimators of traffic intensity, measures of system performance, minimum posterior risk, and minimum Bayes risk associated with these estimators are derived. Also, the Bayes estimator of traffic intensity and its risk function are derived under LINEX loss function. [ABSTRACT FROM AUTHOR]

By considering an M|Er|1 queueing model, the maximum likelihood and consistent estimators of arrival and service parameters are obtained by observing interarrival and service times in the system. Bayes estimators of the parameters both under squared error loss function (SELF) and entropy loss function along with minimum posterior risk and minimum Bayes risk associated with the estimators under SELF are derived. Further, Bayes estimator, minimum posterior risk and minimum Bayes risk of the expected number of entity arrivals in the system under SELF are obtained. An expression for the Bayes estimator of the expected number of entity arrivals in the system under LINEX loss function is also derived. Simulation study to illustrate the performance of the proposed estimators is carried out. [ABSTRACT FROM AUTHOR]