Maximum Entropy Estimation of Transition Probabilities of Reversible Markov Chains
作者： Erik Van der Straeten
DOI: 10.3390/E11040867
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摘要: In this paper, we develop a general theory for the estimation of transition probabilities reversible Markov chains using maximum entropy principle. A broad range physical models can be studied within approach. We use one-dimensional classical spin systems to illustrate theoretical ideas. The examples in paper are: Ising model, Potts model and Blume-Emery-Griffiths model.
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