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

Maximum Entropy Estimation of Transition Probabilities of Reversible Markov Chains

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 maximum entropy principle; Markov chain; parameter estimation; statistical mechanics; spin chain models; thermodynamics
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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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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