1. Efficient computation and statistical assessment of transfer entropy
- Author
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Patrick eBoba, Dominik eBollmann, Daniel eSchoepe, Nora eWester, Jan eWiesel, and Kay eHamacher
- Subjects
Information Theory ,complex systems ,causality ,time series analysis ,transfer entropy ,bootstrapping ,Physics ,QC1-999 - Abstract
The analysis of complex systems frequently poses the challenge to distinguish correlation from causation. Statistical physics hasinspired 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.
- Published
- 2015
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