Iterative Methods for Computing Stationary Distributions of Nearly Completely Decomposable Markov Chains
Copyright policy )Iterative Methods for Computing Stationary Distributions of Nearly Completely Decomposable Markov Chains
We propose new methods which combine aggregation with point and block iterative techniques for computing the stationary probability vector of a finite ergodic Markov chain. These techniques are also compared numerically with several methods which have recently appeared in the literature for the class of nearly completely decomposable Markov chains.
nearly completely decomposable Markov chains, Probabilistic methods, stochastic differential equations, computing the stationary probability vector of a finite ergodic Markov chain, Markov chains (discrete-time Markov processes on discrete state spaces), point and block iterative methods
nearly completely decomposable Markov chains, Probabilistic methods, stochastic differential equations, computing the stationary probability vector of a finite ergodic Markov chain, Markov chains (discrete-time Markov processes on discrete state spaces), point and block iterative methods
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