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Reliable detection of directional couplings using rank statistics Daniel Chicharro and Ralph G. Andrzejak
 

Summary: Reliable detection of directional couplings using rank statistics
Daniel Chicharro and Ralph G. Andrzejak
Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, 08018 Spain
Received 14 January 2009; revised manuscript received 16 April 2009; published 27 August 2009
To detect directional couplings from time series various measures based on distances in reconstructed state
spaces were introduced. These measures can, however, be biased by asymmetries in the dynamics' structure,
noise color, or noise level, which are ubiquitous in experimental signals. Using theoretical reasoning and
results from model systems we identify the various sources of bias and show that most of them can be
eliminated by an appropriate normalization. We furthermore diminish the remaining biases by introducing a
measure based on ranks of distances. This rank-based measure outperforms existing distance-based measures
concerning both sensitivity and specificity for directional couplings. Therefore, our findings are relevant for a
reliable detection of directional couplings from experimental signals.
DOI: 10.1103/PhysRevE.80.026217 PACS number s : 05.45.Tp, 05.45.Xt
I. INTRODUCTION
A detection of directional couplings between two dynami-
cal systems X and Y from the analysis of signals measured
from them is key to an understanding of many dynamics in
nature. Assuming X and Y to be linear stochastic Gaussian
processes, the concept of Granger causality 1 can be imple-
mented using linear regression or autoregressive modeling.

  

Source: Andrzejak, Ralph Gregor - Departament de Tecnologia, Universitat Pompeu Fabra

 

Collections: Computer Technologies and Information Sciences