Abstract
In this paper, we consider a set of individual M/M/1 queues in which variations in both arrival rates and service rates are partly explained by some covariates representing associated characteristics of individual queues. The random error that takes into account the remaining variation is assumed to follow a gamma distribution. Bayes and empirical Bayes procedures are suggested to make inferences concerning individual traffic intensity parameters that can be applied to several industrial queueing problems.
| Original language | English |
|---|---|
| Pages (from-to) | 383-401 |
| Number of pages | 19 |
| Journal | Queueing Systems |
| Volume | 22 |
| Issue number | 3-4 |
| DOIs | |
| Publication status | Published - 1996 Jan 1 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Management Science and Operations Research
- Computational Theory and Mathematics
Cite this
}
Empirical bayesian analysis for traffic intensity : M/M/1 queues with covariates. / Sohn, So Young.
In: Queueing Systems, Vol. 22, No. 3-4, 01.01.1996, p. 383-401.Research output: Contribution to journal › Article
TY - JOUR
T1 - Empirical bayesian analysis for traffic intensity
T2 - M/M/1 queues with covariates
AU - Sohn, So Young
PY - 1996/1/1
Y1 - 1996/1/1
N2 - In this paper, we consider a set of individual M/M/1 queues in which variations in both arrival rates and service rates are partly explained by some covariates representing associated characteristics of individual queues. The random error that takes into account the remaining variation is assumed to follow a gamma distribution. Bayes and empirical Bayes procedures are suggested to make inferences concerning individual traffic intensity parameters that can be applied to several industrial queueing problems.
AB - In this paper, we consider a set of individual M/M/1 queues in which variations in both arrival rates and service rates are partly explained by some covariates representing associated characteristics of individual queues. The random error that takes into account the remaining variation is assumed to follow a gamma distribution. Bayes and empirical Bayes procedures are suggested to make inferences concerning individual traffic intensity parameters that can be applied to several industrial queueing problems.
UR - http://www.scopus.com/inward/record.url?scp=0030518842&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0030518842&partnerID=8YFLogxK
U2 - 10.1007/BF01149180
DO - 10.1007/BF01149180
M3 - Article
AN - SCOPUS:0030518842
VL - 22
SP - 383
EP - 401
JO - Queueing Systems
JF - Queueing Systems
SN - 0257-0130
IS - 3-4
ER -