A divide and conquer approach to computing the mean first passage matrix for Markov chains via Perron complement reductions
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Publication:4828880
DOI10.1002/nla.242zbMath1055.65015OpenAlexW2013095747MaRDI QIDQ4828880
Jianhong Xu, Michael Neumann, Stephen J. Kirkland
Publication date: 26 November 2004
Published in: Numerical Linear Algebra with Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/nla.242
Computational methods in Markov chains (60J22) Numerical analysis or methods applied to Markov chains (65C40)
Related Items (7)
Localization of Perron roots ⋮ Robust power series algorithm for epistemic uncertainty propagation in Markov chain models ⋮ An iterative algorithm for computing mean first passage times of Markov chains ⋮ Improved bounds for a condition number for Markov chains ⋮ Properties for the Perron complement of three known subclasses of \(H\)-matrices ⋮ Development of computational algorithm for multiserver queue with renewal input and synchronous vacation ⋮ Stationary distributions and mean first passage times of perturbed Markov chains
Cites Work
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- The Role of the Group Generalized Inverse in the Theory of Finite Markov Chains
- Stochastic Complementation, Uncoupling Markov Chains, and the Theory of Nearly Reducible Systems
- Cutpoint Decoupling and First Passage Times for Random Walks on Graphs
- The Group Inverse Associated with an Irreducible Periodic Nonnegative Matrix
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