The convergence of sums of transition probabilities of a positive recurrent Markov chain.
E. Nummelin (1981)
Mathematica Scandinavica
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Displaying similar documents to “The central limit theorem for Markov chains with the simultatneous total variation convergence of the chain.”
The convergence of sums of transition probabilities of a positive recurrent Markov chain.
From shuffling cards to walking around the building: An introduction to modern Markov chain theory.
Diaconis, Persi (1998)
Documenta Mathematica
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The discrete skeleton method and a total variation limit theorem for continous-time Markov processes.
E. Nummelin (1978)
Mathematica Scandinavica
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On strong Markov duals.
S.E. Graversen, Murali Rao (1981)
Mathematica Scandinavica
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The Kendall theorem and its application to the geometric ergodicity of Markov chains
Witold Bednorz (2013)
Applicationes Mathematicae
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We give an improved quantitative version of the Kendall theorem. The Kendall theorem states that under mild conditions imposed on a probability distribution on the positive integers (i.e. a probability sequence) one can prove convergence of its renewal sequence. Due to the well-known property (the first entrance last exit decomposition) such results are of interest in the stability theory of time-homogeneous Markov chains. In particular this approach may be used to measure rates of convergence...
Simple Markov chains
O. Adelman (1976)
Annales scientifiques de l'Université de Clermont. Mathématiques
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Geometric ergodicity for a class of Markov chains
E. Nummelin, R. L. Tweedie (1976)
Annales scientifiques de l'Université de Clermont. Mathématiques
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Reduction of absorbing Markov chain
Mariusz Górajski (2009)
Annales UMCS, Mathematica
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In this paper we consider an absorbing Markov chain with finite number of states. We focus especially on random walk on transient states. We present a graph reduction method and prove its validity. Using this method we build algorithms which allow us to determine the distribution of time to absorption, in particular we compute its moments and the probability of absorption. The main idea used in the proofs consists in observing a nondecreasing sequence of stopping times. Random walk on...
The tail structure of nonhomogeneous finite state Markov chains: survey
Marius Losifescu (1979)
Banach Center Publications
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Conditional Markov chains - construction and properties
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.
Why the Kemeny Time is a constant
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.