2017
DOI: 10.3390/e19070372
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Transfer Entropy for Nonparametric Granger Causality Detection: An Evaluation of Different Resampling Methods

Abstract: Abstract:The information-theoretical concept transfer entropy is an ideal measure for detecting conditional independence, or Granger causality in a time series setting. The recent literature indeed witnesses an increased interest in applications of entropy-based tests in this direction. However, those tests are typically based on nonparametric entropy estimates for which the development of formal asymptotic theory turns out to be challenging. In this paper, we provide numerical comparisons for simulation-based… Show more

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Cited by 12 publications
(10 citation statements)
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“…This traditional surrogate methodology uses a phase randomization of the Fourier transform of the original data to preserve the linear correlations. Nevertheless, as discussed and analysed rigorously in Diks and Fang 106 ; these methods are not suitable for detecting significance when using entropy measures, as discussed extensively 107,108 . In view of these problems, Quiroga and colleagues proposed the circular time-shifted surrogates method, which is a method using surrogates that can be used for causality measurements 23 .…”
Section: Neuroimaging Analysis Tools and Methods Normalized Directedmentioning
confidence: 99%
“…This traditional surrogate methodology uses a phase randomization of the Fourier transform of the original data to preserve the linear correlations. Nevertheless, as discussed and analysed rigorously in Diks and Fang 106 ; these methods are not suitable for detecting significance when using entropy measures, as discussed extensively 107,108 . In view of these problems, Quiroga and colleagues proposed the circular time-shifted surrogates method, which is a method using surrogates that can be used for causality measurements 23 .…”
Section: Neuroimaging Analysis Tools and Methods Normalized Directedmentioning
confidence: 99%
“…This traditional surrogate methodology uses a phase randomisation of the Fourier transform of the original data in order to preserve the linear correlations. Nevertheless, as discussed and analysed rigorously in Diks and Fang (Diks and Fang, 2017); these methods are not suitable for detecting significance when using entropy measures, as discussed extensively (Faes et al, 2008;Hinich et al, 2005). In view of these problems, Quiroga and colleagues proposed the circular time shifted surrogates method, which is a robust method using surrogates that can be used for causality measurements (Quiroga et al, 2002).…”
Section: ܺ ܻmentioning
confidence: 99%
“…Establishing asymptotic distribution theory for a fully nonparametric transfer entropy measure is challenging, if not impossible. Diks and Fang [ 22 ] provide numerical comparisons to gain some insights into the statistical behavior of nonparametric transfer entropy-based tests.…”
Section: Introductionmentioning
confidence: 99%