Entropy 2009, 11(4), 867-887; doi:10.3390/e11040867
Article

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
Received: 21 September 2009; Accepted: 10 November 2009 / Published: 17 November 2009
(This article belongs to the Special Issue Maximum Entropy)
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Abstract: 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.
Keywords: maximum entropy principle; Markov chain; parameter estimation; statistical mechanics; spin chain models; thermodynamics

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MDPI and ACS Style

Van der Straeten, E. Maximum Entropy Estimation of Transition Probabilities of Reversible Markov Chains. Entropy 2009, 11, 867-887.

AMA Style

Van der Straeten E. Maximum Entropy Estimation of Transition Probabilities of Reversible Markov Chains. Entropy. 2009; 11(4):867-887.

Chicago/Turabian Style

Van der Straeten, Erik. 2009. "Maximum Entropy Estimation of Transition Probabilities of Reversible Markov Chains." Entropy 11, no. 4: 867-887.

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