Causality in Time Series: Its Detection and Quantification by Means of Information Theory.

Causality in Time Series: Its Detection and Quantification by Means of Information Theory.

Abstract

While studying complex systems, one of the fundamental questions is to identify causal relationships (i.e., which system drives which) between relevant subsystems. In this paper, we focus on information-theoretic approaches for causality detection by means of directionality index based on mutual information estimation. We briefly review the current methods for mutual information estimation from the point of view of their consistency. We also present some arguments from recent literature, supporting the usefulness of the information-theoretic tools for causality detection.

Grafik Top
Authors
  • Schindlerova, Katerina
Grafik Top
Shortfacts
Category
Book Section/Chapter
Divisions
Data Mining
Subjects
Informatik Allgemeines
Title of Book
Information Theory and Statistical Learning
ISSN/ISBN
978-0-387-84816-7
Page Range
pp. 183-207
Date
2009
Official URL
http://link.springer.com/chapter/10.1007/978-0-387...
Export
Grafik Top