Franco Giannessi (2002)
RAIRO - Operations Research - Recherche Opérationnelle
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A problem (arisen from applications to networks) is posed about the principal minors of the matrix of transition probabilities of a Markov chain.
Tomasz R. Bielecki, Jacek Jakubowski, Mariusz Niewęgłowski (2015)
Banach Center Publications
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In this paper we study finite state conditional Markov chains (CMCs). We give two examples of CMCs, one which admits intensity, and another one, which does not admit an intensity. We also give a sufficient condition under which a doubly stochastic Markov chain is a CMC. In addition we provide a method for construction of conditional Markov chains via change of measure.
Franco Giannessi (2010)
RAIRO - Operations Research
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A problem (arisen from applications to networks) is posed about the principal minors of the matrix of transition probabilities of a Markov chain.
Marius Losifescu (1979)
Banach Center Publications
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O. Adelman (1976)
Annales scientifiques de l'Université de Clermont. Mathématiques
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Takacs, Christiane (2006)
Mathematica Pannonica
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Raúl Montes-de-Oca, Alexander Sakhanenko, Francisco Salem-Silva (2003)
Applicationes Mathematicae
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We analyse a Markov chain and perturbations of the transition probability and the one-step cost function (possibly unbounded) defined on it. Under certain conditions, of Lyapunov and Harris type, we obtain new estimates of the effects of such perturbations via an index of perturbations, defined as the difference of the total expected discounted costs between the original Markov chain and the perturbed one. We provide an example which illustrates our analysis.
Piotr Pokarowski (1999)
Applicationes Mathematicae
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This paper is devoted to computational problems related to Markov chains (MC) on a finite state space. We present formulas and bounds for characteristics of MCs using directed forest expansions given by the Matrix Tree Theorem. These results are applied to analysis of direct methods for solving systems of linear equations, aggregation algorithms for nearly completely decomposable MCs and the Markov chain Monte Carlo procedures.
Karl Gustafson, Jeffrey J. Hunter (2016)
Special Matrices
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We present a new fundamental intuition forwhy the Kemeny feature of a Markov chain is a constant. This new perspective has interesting further implications.