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Continuous-time Markov chains

  • Mimmo Iannelli
  • Andrea Pugliese
Chapter
Part of the UNITEXT book series (UNITEXT, volume 79)

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.

Keywords

Markov Chain Infinitesimal Transition Matrix Countable State Space Forward Kolmogorov Equation Absorbing State 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    1. Anderson, W.J.: Continuous-time Markov Chains, Springer, New York (1991)CrossRefzbMATHGoogle Scholar
  2. 2.
    2. Liggett, T.M.: Continuos-time Markov processes: an introduction, American Mathematical Soc. (2010)Google Scholar
  3. 3.
    3. Norris, J.R.: Markov Chains. Cambridge University Press, Cambridge (1997)CrossRefzbMATHGoogle Scholar
  4. 4.
    4. Taylor, H.M., Karlin, S.: An Introduction to Stochastic Modeling, Academic Press, New York (1998)zbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Mimmo Iannelli
    • 1
  • Andrea Pugliese
    • 1
  1. 1.Department of MathematicsUniversity of TrentoItaly

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