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Markov Chains

  • Frank A. Haight
Part of the Mathematical Concepts and Methods in Science and Engineering book series (MCSENG, volume 23)

Abstract

Markov chains are the most substantial application of conditional probability which is easily accessible, and, at the same time, they provide an excellent introduction to the more general subject of stochastic processes. A stochastic process is a random variable with a time index (say, Xn, n= 0, 1, 2,...) for discrete time, or a family of random variables (say, X(t), 0<t<∞) for continuous time.

Keywords

Markov Chain Random Walk Transition Matrix Probability Generate Function Stationary Probability Vector 
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

© Plenum Press, New York 1981

Authors and Affiliations

  • Frank A. Haight
    • 1
  1. 1.The Pennsylvania State UniversityPennsylvaniaUSA

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