Let p ij(t) be the probability that a stochastic process takes on value j at “time” t (discrete or continuous), given that it began at time 0 from state i. If p ij(t) approaches a limit p j independent of i at t →∞ for all j, we say that the process is in statistical equilibrium. If a Markov chain has a limiting distribution, then this distribution is identical to the stationary one found by solving π = πP.v Limiting distribution; Markov chains; Markov processes; Stationary distribution; Steady-state distribution.
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© 2001 Kluwer Academic Publishers
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Gass, S.I., Harris, C.M. (2001). Statistical equilibrium. In: Gass, S.I., Harris, C.M. (eds) Encyclopedia of Operations Research and Management Science. Springer, New York, NY. https://doi.org/10.1007/1-4020-0611-X_994
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DOI: https://doi.org/10.1007/1-4020-0611-X_994
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