Transfer Entropy Expressions for a Class of Non-Gaussian Distributions

被引:7
作者
Jafari-Mamaghani, Mehrdad [1 ,2 ]
Tyrcha, Joanna [1 ]
机构
[1] Stockholm Univ, Dept Math, SE-10691 Stockholm, Sweden
[2] Karolinska Inst, Dept Biosci & Nutr, Ctr Biosci, SE-14183 Huddinge, Sweden
基金
瑞典研究理事会; 欧盟第七框架计划;
关键词
Granger causality; information theory; transfer entropy; multivariate distributions; power-law distributions; CAUSALITY;
D O I
10.3390/e16031743
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
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.
引用
收藏
页码:1743 / 1755
页数:13
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