Evaluating Transfer Entropy for Normal and γ-Order Normal Distributions.

Evaluating Transfer Entropy for Normal and γ-Order Normal Distributions.

Abstract

Since its introduction, transfer entropy has become a popular information-theoretic tool for detecting causal inference between two discretized random processes. By means of statistical tools we evaluatethe transfer entropy of stationary processes whose continuous probability distributions are known. We study transfer entropy of processes coming from the family of γ-order generalized normal distribution.Applying Kullback-Leibler divergence we provide explicit expressions of the transfer entropy forprocesses which are normal, as well as for processes from the class of γ-order normal distributions.The results achieved in the paper for continuous time can be applied also to the discrete time case,concretely to the time series whose underlying process distribution is from the discussed classes.

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Authors
  • Schindlerova, Katerina
  • Toulias, Thomas
  • Kitsos, Christos
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Shortfacts
Category
Journal Paper
Divisions
Data Mining
Subjects
Computermethodik Allgemeines
Angewandte Informatik Sonstiges
Informatik Sonstiges
Theoretische Informatik
Journal or Publication Title
British Journal of Mathematics ans Computer Science
ISSN
2231-0851
Publisher
SCIENCEDOMAIN international
Page Range
pp. 1-20
Number
5
Volume
17
Date
July 2016
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