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Accurate calculations of Stationary Distributions and Mean First Passage Times in Markov Renewal Processes and Markov Chains

机译:马尔可夫更新过程和马尔可夫链中平稳分布和平均首次通过时间的精确计算

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This article describes an accurate procedure for computing the mean first passage times of a finiteirreducible Markov chain and a Markov renewal process. The method is a refinement to the Kohlas, Zeit furOper Res, 30, 197–207, (1986) procedure. The technique is numerically stable in that it doesn’t involve subtractions.Algebraic expressions for the special cases of one, two, three and four states are derived.Aconsequenceof the procedure is that the stationary distribution of the embedded Markov chain does not need to be derivedin advance but can be found accurately from the derived mean first passage times. MatLab is utilized to carryout the computations, using some test problems from the literature.
机译:本文介绍了一种计算有限不可约马尔可夫链的平均首次通过时间和马尔可夫更新过程的准确程序。该方法是Kohlas,Zeit furOper Res,30,197–207,(1986)程序的改进。该技术在数值上是稳定的,因为它不涉及减法。得出一,二,三和四个状态的特殊情况的代数表达式。该过程的后果是不需要嵌入马尔可夫链的平稳分布预先导出,但可以从导出的平均第一次通过时间中准确找到。 MatLab利用文献中的一些测试问题来进行计算。

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