This paper presents several numerical methods which may be used to obtain the stationary probability vectors of Markovian models. An example of a nearly decomposable system is considered, and the results obtained by the different methods examined. A post mortem reveals why standard techniques often fail to yield the correct results. Finally, a means of estimating the error inherent in the decomposition of certain models is presented.
A comparison of numerical techniques in Markov modeling
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