Home > Publications
Home University of Twente
Prospective Students
Intranet (internal)

EEMCS EPrints Service

20245 Quasi-stationary distributions
Home Policy Brochure Browse Search User Area Contact Help

van Doorn, E.A. and Pollett, P.K. (2011) Quasi-stationary distributions. Memorandum 1945, Department of Applied Mathematics, University of Twente, Enschede. ISSN 1874-4850

There is a more recent version of this eprint available. Click here to view it.

Full text available as:


472 Kb
PDF (Revised version entitled "Quasi-stationary distributions for discrete-state models", to appear in European Journal of Operational Research)

401 Kb
PDF (Web appendix to "Quasi-stationary distributions for discrete-state models" )

106 Kb
Open Access

Official URL:

Exported to Metis


This paper contains a survey of results related to quasi-stationary distributions, which arise in the setting of stochastic dynamical systems that eventually evanesce, and which may be useful in describing the long-term behaviour of such systems before evanescence. We are concerned mainly with continuous-time Markov chains over a finite or countably infinite state space, since these processes most often arise in applications, but will make reference to results for other processes where appropriate. Next to giving an historical account of the subject, we review the most important results on the existence and identification of quasi-stationary distributions for general Markov chains, and give special attention to birth-death processes and related models. Results on the question of whether a quasi-stationary distribution, given its existence, is indeed a good descriptor of the long-term behaviour of a system before evanescence, are reviewed as well. The paper is concluded with a summary of recent developments in numerical and approximation methods.

Item Type:Internal Report (Memorandum)
Research Group:EWI-SP: Statistics and Probability
Research Program:CTIT-IE&ICT: Industrial Engineering and ICT
Uncontrolled Keywords:Applied probability, Markov processes
ID Code:20245
Deposited On:17 June 2011
More Information:statisticsmetis

Available Versions of this Item

Export this item as:

To correct this item please ask your editor

Repository Staff Only: edit this item