7. Queueing Analysis

  1. David Rios Insua1,
  2. Fabrizio Ruggeri2 and
  3. Michael P. Wiper3

Published Online: 8 APR 2012

DOI: 10.1002/9780470975916.ch7

Bayesian Analysis of Stochastic Process Models

Bayesian Analysis of Stochastic Process Models

How to Cite

Rios Insua, D., Ruggeri, F. and Wiper, M. P. (2012) Queueing Analysis, in Bayesian Analysis of Stochastic Process Models, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470975916.ch7

Author Information

  1. 1

    Department of Statistics and Operations Research Universidad Rey Juan Carlos, Madrid, Spain

  2. 2

    CNR-IMATI, Milan, Italy

  3. 3

    Department of Statistics, Universidad Carlos III de Madrid, Spain

Publication History

  1. Published Online: 8 APR 2012
  2. Published Print: 13 APR 2012

Book Series:

  1. Wiley Series in Probability and Statistics

Book Series Editors:

  1. Walter A. Shewhart and
  2. Samuel S. Wilks

ISBN Information

Print ISBN: 9780470744536

Online ISBN: 9780470975916

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Keywords:

  • Bayesian inference;
  • non-Markovian systems;
  • queueing analysis

Summary

This chapter examines Bayesian inference and prediction for some of the most important queueing systems, as well as some typical decision-making problems in queueing systems such as the selection of the number of servers. It introduces the basic outline of a queueing system and some of the most important characteristics. Then, the chapter outlines some of the most important queueing models. General aspects of Bayesian inference for queueing systems are briefly commented in the chapter and then, inference for the M/M/1 system is examined. Inference for non-Markovian systems is described. The chapter analyzes decision problems for queueing systems and then, a case study on hospital bed optimization is presented.

Controlled Vocabulary Terms

Bayesian inference; continuous-time Markov process