Computation of Invariant Measures and Stationary Expectations for Markov Chains with Block-Band Transition Matrix

Hendrik Baumann and Thomas Hanschke

Journal of Applied Mathematics, 2020, vol. 2020, 1-16

Abstract:

This paper deals with the computation of invariant measures and stationary expectations for discrete-time Markov chains governed by a block-structured one-step transition probability matrix. The method generalizes in some respect Neuts’ matrix-geometric approach to vector-state Markov chains. The method reveals a strong relationship between Markov chains and matrix continued fractions which can provide valuable information for mastering the growing complexity of real-world applications of large-scale grid systems and multidimensional level-dependent Markov models. The results obtained are extended to continuous-time Markov chains.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnljam:4318906

DOI: 10.1155/2020/4318906

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