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

Salgado-García, R. ; Maldonado, Cesar

Chaos (Woodbury, N.Y.), 2021-01, Vol.31 (1), p.013131-013131 [Periódico revisado por pares]

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Título:
Estimating entropy rate from censored symbolic time series: A test for time-irreversibility
Autor: Salgado-García, R. ; Maldonado, Cesar
Assuntos: Deoxyribonucleic acid ; DNA ; Entropy ; Estimation ; Markov chains ; Parameter estimation ; Statistical tests ; Time series
É parte de: Chaos (Woodbury, N.Y.), 2021-01, Vol.31 (1), p.013131-013131
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Descrição: 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.
Editor: United States: American Institute of Physics
Idioma: Inglês

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