TITLE:
Comparison of Different Confidence Intervals of Intensities for an Open Queueing Network with Feedback
AUTHORS:
Vinayak Kawaduji Gedam, Suresh Bajirao Pathare
KEYWORDS:
Coverage Percentage; Relative Coverage; Bayesian Bootstrap; Bias-Corrected and Accelerated Bootstrap; Percentile Bootstrap; Standard Bootstrap
JOURNAL NAME:
American Journal of Operations Research,
Vol.3 No.2,
March
29,
2013
ABSTRACT:
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.