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Open AccessArticle

Maximum Entropy Estimation of Transition Probabilities of Reversible Markov Chains

Queen Mary University of London, School of Mathematical Sciences, Mile End Road, London E1 4NS, UK
Entropy 2009, 11(4), 867-887; https://doi.org/10.3390/e11040867
Received: 21 September 2009 / Accepted: 10 November 2009 / Published: 17 November 2009
(This article belongs to the Special Issue Maximum Entropy)
In this paper, we develop a general theory for the estimation of the transition probabilities of reversible Markov chains using the maximum entropy principle. A broad range of physical models can be studied within this approach. We use one-dimensional classical spin systems to illustrate the theoretical ideas. The examples studied in this paper are: the Ising model, the Potts model and the Blume-Emery-Griffiths model. View Full-Text
Keywords: maximum entropy principle; Markov chain; parameter estimation; statistical mechanics; spin chain models; thermodynamics maximum entropy principle; Markov chain; parameter estimation; statistical mechanics; spin chain models; thermodynamics
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Van der Straeten, E. Maximum Entropy Estimation of Transition Probabilities of Reversible Markov Chains. Entropy 2009, 11, 867-887.

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