Advances in Applied Probability · 1984 · 59 citations · 7 references
EngineeringComputer ScienceMathematicsProbability TheoryStochastic ProcessesTheory Of ComputationMarkov ChainsMarkov ProcessesProbability InequalitiesStationary ProcessesAggregationFinite Markov ChainsStationary Distributions
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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The Algebraic Eigenvalue Problem
E. I., J. H. Wilkinson · Mathematics of Computation · 1966 · 5.2K citations
Aggregation of Variables in Dynamic Systems
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Paul J. Schweitzer · Journal of Applied Probability · 1968 · 88 citations