
Let A be a stochastic matrix and ε a positive number. We consider all stochastic matrices within ε of A and their corresponding stochastic eigenvectors. A convex polytope containing these vectors is described. An efficient algorithm for computing bounds on the components of these vectors is also given. The work is compared to previous such work done by the author and by Courtois and Semai.
approximation of stochastic eigenvectors, convex polytope, Markov chains (discrete-time Markov processes on discrete state spaces), Approximation by convex sets, Stochastic matrices
approximation of stochastic eigenvectors, convex polytope, Markov chains (discrete-time Markov processes on discrete state spaces), Approximation by convex sets, Stochastic matrices
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