Efficient computation and statistical assessment of transfer entropy

Frontiers in Physics

Hamacher, Kay¹  Boba, Patrick¹  Bollmann, Dominik²  Schoepe, Daniel²  Wester, Nora²  Wiesel, Jan² 

[1] Computational Biology and Simulation, Department of Biology, Technical University Darmstadt, Darmstadt, Germany;Department of Computer Science, Technical University Darmstadt, Darmstadt, Germany

关键词: transfer entropy;    complex systems;    time series analysis;    Information Theory;    causality;    bootstrapping;   

DOI  :  10.3389/fphy.2015.00010

学科分类：物理（综合）

来源: Frontiers

【 摘 要 】

The analysis of complex systems frequently poses the challenge to distinguish correlation from causation. Statistical physics has inspired very promising approaches to search for correlations in time series; the transfer entropy in particular (Hlavackova-Schindler et al., 2007). Now, methods from computational statistics can quantitatively assign significance to such correlation measures. In this study, we propose and apply a procedure to statistically assess transfer entropies by one-sided tests. We introduce to null models of vanishing correlations for time series with memory. We implemented them in an OpenMP-based, parallelized C++ package for multi-core CPUs. Using template meta-programming, we enable a compromise between memory and run time efficiency.

【 授权许可】

CC BY