Assessing significance of information flow in high dimensional dynamical systems with few data

Ross P. Anderson, Maurizio Porfiri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Information-theoretical notions of causality provide a model-free app roach to identification of the magnitude and direction of influence among sub-components of a stochastic dynamical system. In addition to detecting causal influences, any effective test should also report the level of statistical significance of the finding. Here, we focus on transfer entropy, which has recently been considered for causality detection in a variety of fields based on statistical significance tests that are valid only in the asymptotic regime, that is, with enormous amounts of data. In the interest of app lications with limited available data, we develop a non-asymptotic theory for the probability distribution of the difference between the empirically-estimated transfer entropy and the true transfer entropy. Based on this result, we additionally demonstrate an app roach for statistical hypothesis testing for directed information flow in dynamical systems with a given number of observed time steps.

Original languageEnglish (US)
Title of host publicationDynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing
PublisherAmerican Society of Mechanical Engineers
Volume2
ISBN (Print)9780791846193
DOIs
StatePublished - 2014
EventASME 2014 Dynamic Systems and Control Conference, DSCC 2014 - San Antonio, United States
Duration: Oct 22 2014Oct 24 2014

Other

OtherASME 2014 Dynamic Systems and Control Conference, DSCC 2014
CountryUnited States
CitySan Antonio
Period10/22/1410/24/14

Fingerprint

Application programs
Dynamical systems
Entropy
Statistical tests
Probability distributions
Identification (control systems)
Testing

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

Cite this

Anderson, R. P., & Porfiri, M. (2014). Assessing significance of information flow in high dimensional dynamical systems with few data. In Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing (Vol. 2). [5865] American Society of Mechanical Engineers. https://doi.org/10.1115/DSCC2014-5865

Assessing significance of information flow in high dimensional dynamical systems with few data. / Anderson, Ross P.; Porfiri, Maurizio.

Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing. Vol. 2 American Society of Mechanical Engineers, 2014. 5865.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Anderson, RP & Porfiri, M 2014, Assessing significance of information flow in high dimensional dynamical systems with few data. in Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing. vol. 2, 5865, American Society of Mechanical Engineers, ASME 2014 Dynamic Systems and Control Conference, DSCC 2014, San Antonio, United States, 10/22/14. https://doi.org/10.1115/DSCC2014-5865
Anderson RP, Porfiri M. Assessing significance of information flow in high dimensional dynamical systems with few data. In Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing. Vol. 2. American Society of Mechanical Engineers. 2014. 5865 https://doi.org/10.1115/DSCC2014-5865
Anderson, Ross P. ; Porfiri, Maurizio. / Assessing significance of information flow in high dimensional dynamical systems with few data. Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing. Vol. 2 American Society of Mechanical Engineers, 2014.
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