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Estimating entropy rate from censored symbolic time series: A test for time-irreversibility

dc.contributor.authorSalgado García, Raúl
dc.contributor.authorMaldonado Ahumada, César Octavio
dc.contributor.author000
dc.date.accessioned2022-02-24T20:00:33Z
dc.date.available2022-02-24T20:00:33Z
dc.date.issued2021
dc.identifier.citationR. Salgado-García and Cesar Maldonado. "Estimating entropy rate from censored symbolic time series: A test for time-irreversibility", Chaos 31, 013131 (2021); https://doi.org/10.1063/5.0032515
dc.identifier.urihttp://hdl.handle.net/11627/5733
dc.description.abstract"In this work, we introduce a method for estimating the entropy rate and the entropy production rate from a finite symbolic time series. From the point of view of statistics, estimating entropy from a finite series can be interpreted as a problem of estimating parameters of a distribution with a censored or truncated sample. We use this point of view to give estimations of the entropy rate and the entropy production rate, assuming that they are parameters of a (limit) distribution. The last statement is actually a consequence of the fact that the distribution of estimations obtained from recurrence-time statistics satisfies the central limit theorem. We test our method using a time series coming from Markov chain models, discrete-time chaotic maps, and a real DNA sequence from the human genome."
dc.publisherAmerican Institute of Physics
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectSharp error terms
dc.subjectFluctuations
dc.subjectRecurrence
dc.subject.classificationMATEMÁTICAS
dc.titleEstimating entropy rate from censored symbolic time series: A test for time-irreversibility
dc.typearticle
dc.identifier.doihttps://doi.org/10.1063/5.0032515
dc.rights.accessAcceso Abierto


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional