Numerical Iteration for Stationary Probabilities of Markov Chains

  • Na, Seongryong (Department of Information and Statistics, Yonsei University)
  • Received : 2014.08.19
  • Accepted : 2014.11.11
  • Published : 2014.11.30


We study numerical methods to obtain the stationary probabilities of continuous-time Markov chains whose embedded chains are periodic. The power method is applied to the balance equations of the periodic embedded Markov chains. The power method can have the convergence speed of exponential rate that is ambiguous in its application to original continuous-time Markov chains since the embedded chains are discrete-time processes. An illustrative example is presented to investigate the numerical iteration of this paper. A numerical study shows that a rapid and stable solution for stationary probabilities can be achieved regardless of periodicity and initial conditions.


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