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Iterative aggregation/disaggregation methods for computing some characteristics of Markov chains. II: Fast convergence. (English) Zbl 1025.65012
Summary: A class of iterative aggregation/disaggregation methods (IAD) for computation of some important characteristics of Markov chains such as stationary probability vectors and mean first passage times matrices is presented and convergence properties of the corresponding algorithms are analyzed. Particular attention is focused on the fast convergence. Some classes of problems are identified for which the IAD methods return exact solutions after one single iteration sweap.
For part I see I. Marek and P. Mayer, Lect. Notes Comput. Sci. 2179, 68–80 (2001; Zbl 1031.65020).

MSC:
65C40 Numerical analysis or methods applied to Markov chains
60J22 Computational methods in Markov chains
Software:
MARCA
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References:
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