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The joint distribution of sojourn times in finite Markov processes
24
Citations
8
References
1992
Year
EngineeringMarkov Decision ProcessesStochastic PhenomenonTime DiscretizationStochastic Hybrid SystemMarkov ChainsReliability EngineeringStochastic ProcessesSystems EngineeringCumulative Distribution FunctionStochastic GeometryStatisticsProbabilistic SystemStochastic SystemMarkov ProcessesComputer EngineeringStochastic Dynamical SystemProbability TheoryComputer ScienceFinite Markov ProcessesEntropyNatural SciencesProbabilistic VerificationMarkov Kernel
Rubino and Sericola (1989c) derived expressions for the m th sojourn time distribution associated with a subset of the state space of a homogeneous irreducible Markov chain for both the discrete- and continuous-parameter cases. In the present paper, it is shown that a suitable probabilistic reasoning using absorbing Markov chains can be used to obtain respectively the probability mass function and the cumulative distribution function of the joint distribution of the first m sojourn times. A concise derivation of the continuous-time result is achieved by deducing it from the discrete-time formulation by time discretization. Generalizing some further recent results by Rubino and Sericola (1991), the joint distribution of sojourn times for absorbing Markov chains is also derived. As a numerical example, the model of a fault-tolerant multiprocessor system is considered.
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