Non-parametric directionality analysis: extension for removal of a single common predictor and application to time series

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Non-parametric directionality analysis: extension for removal of a single common predictor and application to time series

BACKGROUND: The ability to infer network structure from multivariate neuronal signals is central to computational neuroscience. Directed network analyses typically use parametric approaches based on auto-regressive (AR) models, where networks are constructed from estimates of AR model parameters. Ho...

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Bibliographic Details
Main Authors:	Halliday, David M., Senik, Mohd Harizal, Stevenson, Carl W., Mason, Robert
Format:	Article
Published:	Elsevier 2016
Subjects:	Directionality Partial Coherence Non parametric Time series Point process Conditional independence Granger causality
Online Access:	https://eprints.nottingham.ac.uk/38489/

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