2000 | OriginalPaper | Buchkapitel
Transient Solutions for Markov Chains
verfasst von : Edmundo de Souza e Silva, H. Richard Gail
Erschienen in: Computational Probability
Verlag: Springer US
Enthalten in: Professional Book Archive
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Much of the theory developed for solving Markov chain models is devoted to obtaining steady state measures, that is, measures for which the observation interval (0, t) is “sufficiently large” (t → ∞). These measures are indeed approximations of the behavior of the system for a finite, but long, time interval, where long means with respect to the interval of time between occurrences of events in the system. However, an increasing number of applications requires the calculation of measures during a relatively “short” period of time. These are the so-called transient measures. In these cases the steady state measures are not good approximations for the transient, and one has to resort to different techniques to obtain the desired quantities.