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ML and Bayes estimation in a two-phase tandem queue with a second optional service and random feedback

机译:具有第二个可选服务和随机反馈的两阶段串联队列中的ML和贝叶斯估计

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摘要

In this article, we consider a two-phase tandem queueing model with a second optional service and random feedback. The first phase of service is essential for all customers and after the completion of the first phase of service, any customer receives the second phase of service with probability , feedback to the tail of the first queue with probability if the service is not successful and leaves the system with probability 1 - - . In this model, our main purpose is to estimate the parameters of the model, traffic intensity, and mean system size, in the steady state, via maximum likelihood and Bayesian methods. Furthermore, we find asymptotic confidence intervals for mean system size. Finally, by a simulation study, we compute the confidence levels and mean length for asymptotic confidence intervals of mean system size with a nominal level 0.95.
机译:在本文中,我们考虑具有第二个可选服务和随机反馈的两阶段串联排队模型。服务的第一阶段对所有客户都是必不可少的,在完成第一阶段的服务后,任何客户都可以接受第二阶段的服务,如果服务不成功并离开,则有机会反馈到第一队列的尾部系统的概率为1--。在此模型中,我们的主要目的是通过最大似然法和贝叶斯方法估计稳态下的模型参数,交通强度和平均系统大小。此外,我们找到了平均系统大小的渐近置信区间。最后,通过仿真研究,我们计算了具有名义水平0.95的平均系统大小的渐近置信区间的置信度和平均长度。

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