Abstract
We present here a short summary of the parts of the theory of Markov processes with countable state space that is used in the chapters describing stochastic models of populations. The presentation will be restricted to Markov process that are generated by an infinitesimal transition matrix, as discussed below.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
1. Anderson, W.J.: Continuous-time Markov Chains, Springer, New York (1991)
2. Liggett, T.M.: Continuos-time Markov processes: an introduction, American Mathematical Soc. (2010)
3. Norris, J.R.: Markov Chains. Cambridge University Press, Cambridge (1997)
4. Taylor, H.M., Karlin, S.: An Introduction to Stochastic Modeling, Academic Press, New York (1998)
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Iannelli, M., Pugliese, A. (2014). Continuous-time Markov chains. In: An Introduction to Mathematical Population Dynamics. UNITEXT(), vol 79. Springer, Cham. https://doi.org/10.1007/978-3-319-03026-5_13
Download citation
DOI: https://doi.org/10.1007/978-3-319-03026-5_13
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03025-8
Online ISBN: 978-3-319-03026-5
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)