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Introduction to Focus Issue: Causation inference and information flow in dynamical systems: Theory and applications

Bollt, Erik M. and Sun, Jie and Runge, Jakob (2018) Introduction to Focus Issue: Causation inference and information flow in dynamical systems: Theory and applications. Chaos, 28 (7), 075201. American Institute of Physics (AIP). ISSN 1054-1500

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Official URL: http://aip.scitation.org/doi/10.1063/1.5046848

Abstract

Questions of causation are foundational across science and often relate further to problems of control, policy decisions, and forecasts. In nonlinear dynamics and complex systems science, causation inference and information flow are closely related concepts, whereby information or knowledge of certain states can be thought of as coupling influence onto the future states of other processes in a complex system. While causation inference and information flow are by now classical topics, incorporating methods from statistics and time series analysis, information theory, dynamical systems, and statistical mechanics, to name a few, there remain important advancements in continuing to strengthen the theory, and pushing the context of applications, especially with the ever-increasing abundance of data collected across many fields and systems. This Focus Issue considers different aspects of these questions, both in terms of founding theory and several topical applications.

Item URL in elib:https://elib.dlr.de/126422/
Document Type:Article
Title:Introduction to Focus Issue: Causation inference and information flow in dynamical systems: Theory and applications
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Bollt, Erik M.UNSPECIFIEDUNSPECIFIED
Sun, JieUNSPECIFIEDUNSPECIFIED
Runge, JakobInstitute of Data Sciencehttps://orcid.org/0000-0002-0629-1772
Date:2018
Journal or Publication Title:Chaos
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:28
Page Range:075201
Publisher:American Institute of Physics (AIP)
ISSN:1054-1500
Status:Published
Keywords:causal inference, information theory
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:other
DLR - Research area:Raumfahrt
DLR - Program:R - no assignment
DLR - Research theme (Project):R - no assignment
Location: Jena
Institutes and Institutions:Institute of Data Science > Datamangagement and Analysis
Deposited By: Runge, Jakob
Deposited On:08 Feb 2019 08:11
Last Modified:01 Sep 2019 03:00

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