Publication | Closed Access
Perturbation bounds for the stationary probabilities of a finite Markov chain
59
Citations
7
References
1984
Year
EngineeringComputational ComplexityStochastic AnalysisMarkov Chain Monte CarloStochastic SimulationStochastic ProcessesStochastic GeometryPerturbation BoundsApproximation TheoryDecomposable Markov ChainLower BoundStochastic SystemStochastic Dynamical SystemProbability TheoryFinite Markov ChainMarkov Decision ProcessMarkov KernelPoisson BoundaryStationary DistributionStationary Probabilities
This paper discusses perturbation bounds for the stationary distribution of a finite indecomposable Markov chain. Existing bounds are reviewed. New bounds are presented which more completely exploit the stochastic features of the perturbation and which also are easily computable. Examples illustrate the tightness of the bounds and their application to bounding the error in the Simon–Ando aggregation technique for approximating the stationary distribution of a nearly completely decomposable Markov chain.
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