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Entropy 2015, 17(6), 3738-3751; doi:10.3390/e17063738

Maximum Entropy Rate Reconstruction of Markov Dynamics

1
Department of Computer Science, University of Geneva, Route de Drize 7, 1227 Geneva, Switzerland
2
Department of Theoretical Physics, University of Geneva, Quai Ernest-Ansermet 24,1211 Geneva, Switzerland
*
Author to whom correspondence should be addressed.
Academic Editor: Rick Quax
Received: 5 March 2015 / Revised: 2 June 2015 / Accepted: 4 June 2015 / Published: 8 June 2015
(This article belongs to the Special Issue Information Processing in Complex Systems)
View Full-Text   |   Download PDF [460 KB, uploaded 8 June 2015]   |  

Abstract

We develop ideas proposed by Van der Straeten to extend maximum entropy principles to Markov chains. We focus in particular on the convergence of such estimates in order to explain how our approach makes possible the estimation of transition probabilities when only short samples are available, which opens the way to applications to non-stationary processes. The current work complements an earlier communication by providing numerical details, as well as a full derivation of the multi-constraint two-state and three-state maximum entropy transition matrices. View Full-Text
Keywords: maximum entropy principle; parameter estimation; Markov chain maximum entropy principle; parameter estimation; Markov chain
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. (CC BY 4.0).

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Chliamovitch, G.; Dupuis, A.; Chopard, B. Maximum Entropy Rate Reconstruction of Markov Dynamics. Entropy 2015, 17, 3738-3751.

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