1 Simulating Markov chains

@inproceedings{Sigman20131SM,
  title={1 Simulating Markov chains},
  author={Karl Sigman},
  year={2013}
}
Many stochastic processes used for the modeling of systems in engineering are Markovian, and this makes it relatively easy to simulate from them. Recall, for example, the Binomial Lattice Model for risky assets (stock), or the FIFO delay sequence for the GI/GI/1 queue; those are Markov chains. Here we present a brief introduction to the simulation of Markov chains in general. Our emphasis is on discrete-state chains both in discrete and continuous time, but some examples with a general state… CONTINUE READING

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Choose an initial value, X 0 = i

Choose an initial value, X 0 = i

Go back to 3

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then set i = X n , generate Y i , then set n = n + 1, i = Y i , X n = i, and generate H i ∼ F i and set t = t + H i , t n = t; otherwise set N = n and output

If
then set i = X n , generate Y i , then set n = n + 1, i = Y i , X n = i, and generate H i ∼ F i and set t = t + H i , t n = t; otherwise set N = n and output

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