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Transfer Entropy Expressions for a Class of Non-Gaussian Distributions
Stockholm University, Faculty of Science, Department of Mathematics. Karolinska Institutet, Sweden.
Stockholm University, Faculty of Science, Department of Mathematics.
2014 (English)In: Entropy, ISSN 1099-4300, E-ISSN 1099-4300, Vol. 16, no 3, 1743-1755 p.Article in journal (Refereed) Published
Abstract [en]

Transfer entropy is a frequently employed measure of conditional co-dependence in non-parametric analysis of Granger causality. In this paper, we derive analytical expressions for transfer entropy for the multivariate exponential, logistic, Pareto (type I - IV) and Burr distributions. The latter two fall into the class of fat-tailed distributions with power law properties, used frequently in biological, physical and actuarial sciences. We discover that the transfer entropy expressions for all four distributions are identical and depend merely on the multivariate distribution parameter and the number of distribution dimensions. Moreover, we find that in all four cases the transfer entropies are given by the same decreasing function of distribution dimensionality.

Place, publisher, year, edition, pages
2014. Vol. 16, no 3, 1743-1755 p.
Keyword [en]
Granger causality, information theory, transfer entropy, multivariate distributions, power-law distributions
National Category
Physical Sciences
Identifiers
URN: urn:nbn:se:su:diva-104001DOI: 10.3390/e16031743ISI: 000334248200027OAI: oai:DiVA.org:su-104001DiVA: diva2:720872
Funder
Swedish Research Council, 340-2012-6011EU, FP7, Seventh Framework Programme, 258068
Note

AuthorCount:2;

Available from: 2014-06-02 Created: 2014-05-27 Last updated: 2017-12-05Bibliographically approved

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