Transfer Entropy Expressions for a Class of Non-Gaussian Distributions
2014 (English)In: Entropy, ISSN 1099-4300, E-ISSN 1099-4300, Vol. 16, no 3, 1743-1755 p.Article in journal (Refereed) Published
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.
Granger causality, information theory, transfer entropy, multivariate distributions, power-law distributions
IdentifiersURN: urn:nbn:se:su:diva-104001DOI: 10.3390/e16031743ISI: 000334248200027OAI: oai:DiVA.org:su-104001DiVA: diva2:720872
FunderSwedish Research Council, 340-2012-6011EU, FP7, Seventh Framework Programme, 258068