Oct 7, 2017 · Here, we define a dependency to be any deviation from statistical independence. It is possible for a single multivariate distribution to consist ...
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Sep 5, 2016 · We extend this observation to demonstrate that this is true of all such Shannon information measures when used to analyze multivariate dependencies.
Accurately determining dependency structure is critical to discovering a system's causal orga- nization. We recently showed that the transfer entropy fails in a ...
Accurately determining dependency structure is critical to discovering a system's causal organization. We recently showed that the transfer entropy fails in ...
The vast majority of Shannon information measures are simply inadequate for determining the meaningful dependency structure within joint probability ...
Sep 8, 2016 · They consist of a qualitative and of a quantitative part describing the (in-)dependencies between the variables of interest as a directed ...
Entropy 2017, 19, 531. https://doi.org/10.3390/e19100531. AMA Style. James RG, Crutchfield JP. Multivariate Dependence beyond Shannon Information. Entropy.
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James, R., and Crutchfield, J. (2017). "Multivariate Dependence beyond Shannon Information". Entropy, 19(10), 531.
Jun 20, 2018 · “Multivariate dependence beyond. Shannon information”. In: Entropy 19.10 (2017), p. 531. [14] Paul L Williams and Randall D Beer ...
As seen in Shannon-like Information Measures Are Insensitive to Structural Differences, zero coinformation does not indicate a lack of triadic interactions. If ...