Comparison of Different Confidence Intervals of Intensities for an Open Queueing Network with Feedback

• 作者: Suresh Bajirao Pathare Vinayak Kawaduji Gedam
• 来源期刊: 美国运筹学期刊(英文)
• 学科: 医学
• 关键词: COVERAGE PERCENTAGE Relative COVERAGE BAYESIAN BOOTSTRAP Bias-Corrected and Accelerated BOOTSTRAP Percentile BOOTSTRAP Standard BOOTSTRAP
• 年，卷（期）: 2013,（2）
• 页码范围: 307-327
• 页数: 21页
• 分类号: R73

摘要

In this paper we propose a consistent and asymptotically normal estimator (CAN) of intensities ρ1 , ρ2 for a queueing network with feedback (in which a job may return to previously visited nodes) with distribution-free inter-arrival and service times. Using this estimator and its estimated variance, some 100(1-α)% asymptotic confidence intervals of intensities are constructed. Also bootstrap approaches such as Standard bootstrap, Bayesian bootstrap, Percentile bootstrap and Bias-corrected and accelerated bootstrap are also applied to develop the confidence intervals of intensities. A comparative analysis is conducted to demonstrate performances of the confidence intervals of intensities for a queueing network with short run data.