Efficient computation and statistical assessment of transfer entropy
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...
| 發表在: | Frontiers in Physics |
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| Main Authors: | , , , , , |
| 格式: | Article |
| 語言: | 英语 |
| 出版: |
Frontiers Media S.A.
2015-03-01
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| 主題: | |
| 在線閱讀: | http://journal.frontiersin.org/Journal/10.3389/fphy.2015.00010/full |
| _version_ | 1856906673192435712 |
|---|---|
| author | Patrick eBoba Dominik eBollmann Daniel eSchoepe Nora eWester Jan eWiesel Kay eHamacher |
| author_facet | Patrick eBoba Dominik eBollmann Daniel eSchoepe Nora eWester Jan eWiesel Kay eHamacher |
| author_sort | Patrick eBoba |
| collection | DOAJ |
| container_title | Frontiers in Physics |
| description | 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. |
| format | Article |
| id | doaj-art-1f88e9d8e33e4e4ebeb3e1db62bb5f9b |
| institution | Directory of Open Access Journals |
| issn | 2296-424X |
| language | English |
| publishDate | 2015-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| spelling | doaj-art-1f88e9d8e33e4e4ebeb3e1db62bb5f9b2025-08-19T20:22:09ZengFrontiers Media S.A.Frontiers in Physics2296-424X2015-03-01310.3389/fphy.2015.00010122215Efficient computation and statistical assessment of transfer entropyPatrick eBoba0Dominik eBollmann1Daniel eSchoepe2Nora eWester3Jan eWiesel4Kay eHamacher5TU DarmstadtTU DarmstadtTU DarmstadtTU DarmstadtTU DarmstadtTechnical University DarmstadtThe 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.http://journal.frontiersin.org/Journal/10.3389/fphy.2015.00010/fullInformation Theorycomplex systemscausalitytime series analysistransfer entropybootstrapping |
| spellingShingle | Patrick eBoba Dominik eBollmann Daniel eSchoepe Nora eWester Jan eWiesel Kay eHamacher Efficient computation and statistical assessment of transfer entropy Information Theory complex systems causality time series analysis transfer entropy bootstrapping |
| title | Efficient computation and statistical assessment of transfer entropy |
| title_full | Efficient computation and statistical assessment of transfer entropy |
| title_fullStr | Efficient computation and statistical assessment of transfer entropy |
| title_full_unstemmed | Efficient computation and statistical assessment of transfer entropy |
| title_short | Efficient computation and statistical assessment of transfer entropy |
| title_sort | efficient computation and statistical assessment of transfer entropy |
| topic | Information Theory complex systems causality time series analysis transfer entropy bootstrapping |
| url | http://journal.frontiersin.org/Journal/10.3389/fphy.2015.00010/full |
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