@article{Razak:2014:10.1371/journal.pone.0099462,
author = {Razak, FA and Jensen, HJ},
doi = {10.1371/journal.pone.0099462},
journal = {PLOS One},
title = {Quantifying 'causality' in complex systems: understanding transfer entropy},
url = {http://dx.doi.org/10.1371/journal.pone.0099462},
volume = {9},
year = {2014}
}

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TY  - JOUR
AB  - ‘Causal’ direction is of great importance when dealing with complex systems. Often big volumes of data in the form of time series are available and it is important to develop methods that can inform about possible causal connections between the different observables. Here we investigate the ability of the Transfer Entropy measure to identify causal relations embedded in emergent coherent correlations. We do this by firstly applying Transfer Entropy to an amended Ising model. In addition we use a simple Random Transition model to test the reliability of Transfer Entropy as a measure of ‘causal’ direction in the presence of stochastic fluctuations. In particular we systematically study the effect of the finite size of data sets.
AU  - Razak,FA
AU  - Jensen,HJ
DO  - 10.1371/journal.pone.0099462
PY  - 2014///
SN  - 1932-6203
TI  - Quantifying 'causality' in complex systems: understanding transfer entropy
T2  - PLOS One
UR  - http://dx.doi.org/10.1371/journal.pone.0099462
UR  - http://hdl.handle.net/10044/1/25883
VL  - 9
ER  - 

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