Publication:
Bayesian estimation for the M/G/1 queue using a phase type approximation

Thumbnail Image
Identifiers
URI: http://hdl.handle.net/10016/165
Files
ws013019.pdf (326.45 KB)
Publication date
2001-06
Defense date
Authors
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
Impact
Google Scholar
Export
Research Projects
Organizational Units
Journal Issue
Abstract
This article deals with Bayesian inference and prediction for M/G/1 queueing systems. The general service time density is approximated with a class of Erlang mixtures which are phase type distributions. Given this phase type approximation, an explicit evaluation of measures such as the stationary queue size, waiting time and busy period distributions can be obtained. Given arrival and service data, a Bayesian procedure based on reversible jump Markov Chain Monte Carlo methods is proposed to estimate system parameters and predictive distributions.
Description
Keywords
Bibliographic citation
Collections
DES - Working Papers. Statistics and Econometrics. WS