Statistical inference on traffic intensity in an M / M / 1 queueing system. Issue 4 (2nd October 2018)

• Record Type: Journal Article
• Authors: Choudhury, Amit; Basak, Arpita
• Is Part Of: International journal of management science and engineering management. Volume 13:Issue 4(2018)
• Page Start: 274
• Page End: 279
• Publication Date: 2018-10-02
• Subjects: Classical inference -- confidence interval -- hypothesis testing -- M / M / 1 queue -- traffic intensity; C10 -- C12 -- C13 -- C15 -- C18; Management science -- Periodicals; Engineering -- Management -- Periodicals; Engineering -- Management; Management science; Periodicals; 658.005
• DOI: 10.1080/17509653.2018.1436010
• Languages: English
• ISSNs: 1750-9661

Abstract

Abstract: Traffic intensity is perhaps the most important parameter of the M / M / 1 queueing system. This paper deals with the statistical inference of such a parameter. The maximum likelihood estimator of traffic intensity by observing the number of customers in the system at the departure epoch has been worked out. Confidence intervals and testing of hypotheses have been discussed. An approach to determining sample size has also been presented. While these aspects have been covered in the literature, the methods outlined are not without pitfalls. We propose a simple approach by exploiting a trick by which the M / M / 1 process is linked to the Bernoulli process.