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.
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.
O. Adelman (1976)
Annales scientifiques de l'Université de Clermont. Mathématiques
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Laurent Mazliak (2007)
Revue d'histoire des mathématiques
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We present the letters sent by Wolfgang Doeblin to Bohuslav Hostinský between 1936 and 1938. They concern some aspects of the general theory of Markov chains and the solutions of the Chapman-Kolmogorov equation that Doeblin was then establishing for his PhD thesis.
Marius Losifescu (1979)
Banach Center Publications
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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.
Jeffrey J. Hunter (2016)
Special Matrices
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This article describes an accurate procedure for computing the mean first passage times of a finite irreducible Markov chain and a Markov renewal process. The method is a refinement to the Kohlas, Zeit fur Oper Res, 30, 197–207, (1986) procedure. The technique is numerically stable in that it doesn’t involve subtractions. Algebraic expressions for the special cases of one, two, three and four states are derived.Aconsequence of the procedure is that the stationary distribution of the...
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.