Artículo de Publicación Periódica:
Confidence intervals and hypothesis testing for the Permutation Entropy with an application to epilepsy

dc.contributor.authorTraversaro Varela, Francisco
dc.contributor.authorRedelico, Francisco
dc.date.accessioned2020-06-24T16:38:19Z
dc.date.available2020-06-24T16:38:19Z
dc.date.issued2018-04
dc.description.abstract"In nonlinear dynamics, and to a lesser extent in other fields, a widely used measure of complexity is the Permutation Entropy. But there is still no known method to determine the accuracy of this measure. There has been little research on the statistical properties of this quantity that characterize time series. The literature describes some resampling methods of quantities used in nonlinear dynamics - as the largest Lyapunov exponent - but these seems to fail. In this contribution, we propose a parametric bootstrap methodology using a symbolic representation of the time series to obtain the distribution of the Permutation Entropy estimator. We perform several time series simulations given by well-known stochastic processes: the 1/f α noise family, and show in each case that the proposed accuracy measure is as efficient as the one obtained by the frequentist approach of repeating the experiment. The complexity of brain electrical activity, measured by the Permutation Entropy, has been extensively used in epilepsy research for detection in dynamical changes in electroencephalogram (EEG) signal with no consideration of the variability of this complexity measure. An application of the parametric bootstrap methodology is used to compare normal and pre-ictal EEG signals."en
dc.identifier.issn1007-5704
dc.identifier.urihttp://ri.itba.edu.ar/handle/123456789/2218
dc.language.isoenen
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.cnsns.2017.10.013
dc.subjectEPILEPSIAes
dc.subjectENTROPIAes
dc.subjectELECTROENCEFALOGRAFIAes
dc.subjectANALISIS DE SERIES DE TIEMPOes
dc.subjectPROCESAMIENTO DE SEÑALES DIGITALESes
dc.titleConfidence intervals and hypothesis testing for the Permutation Entropy with an application to epilepsyen
dc.typeArtículos de Publicaciones Periódicases
dc.typeinfo:eu-repo/semantics/acceptedVersion
dspace.entity.typeArtículo de Publicación Periódica
itba.description.filiationFil: Traversaro Varela, Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
itba.description.filiationFil: Traversaro Varela, Francisco. Instituto Tecnológico de Buenos Aires; Argentina.
itba.description.filiationFil: Redelico, Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
itba.description.filiationFil: Redelico, Francisco. Universidad Nacional de Quilmes; Argentina.
itba.description.filiationFil: Traversaro Varela, Francisco. Universidad Nacional de Lanús; Argentina.
itba.description.filiationFil: Redelico, Francisco. Hospital Italiano de Buenos Aires; Argentina.

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