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Stochastic Processes (iii): Markov Chains

  • Warren J. Ewens
  • Gregory R. Grant
Part of the Statistics for Biology and Health book series (SBH)

Abstract

Introductory aspects of the theory of Markov chains were discussed in Chapter 4. In the present chapter further details of the theory of Markov chains will be discussed, first for Markov chains with no absorbing states and second for Markov chains with absorbing states. Our analysis of finite Markov chain theory is often oversimplified, since an examination of some of the subtleties involved in the full theory is not appropriate for bioinformatics. A recent and more complete exposition of the theory can be found in Norris (1997).

Keywords

Markov Chain Stationary Distribution Transition Matrix Relative Entropy Spectral Expansion 
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.

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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Warren J. Ewens
    • 1
  • Gregory R. Grant
    • 2
  1. 1.Department of BiologyUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.Penn Center for Computational BiologyUniversity of PennsylvaniaPhiladelphiaUSA

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