Description length guided nonlinear unified Granger causality analysis [PDF]
Harvard Data Science Review, 2023 Abstract Most Granger causality analysis (GCA) methods still remain a two-stage scheme guided by different mathematical theories; both can actually be viewed as the same generalized model selection issues. Adhering to Occam’s razor, we present a unified GCA (uGCA) based on the minimum description length principle.
Fei Li +3 more
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New Insights into Signed Path Coefficient Granger Causality Analysis [PDF]
Frontiers in Neuroinformatics, 2016 Granger causality analysis, as a time series analysis technique derived from econometrics, has been applied in an ever-increasing number of publications in the field of neuroscience, including fMRI, EEG/MEG, and fNIRS. The present study mainly focuses on
Jian Zhang +3 more
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Granger Causality Analysis of Chignolin Folding. [PDF]
J Chem Theory Comput, 2022 Constantly advancing computer simulations of biomolecules provide huge amounts of data that are difficult to interpret. In particular, obtaining insights into functional aspects of macromolecular dynamics, often related to cascades of transient events, calls for methodologies that depart from the well-grounded framework of equilibrium statistical ...
Sobieraj M, Setny P.
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Bibliometric Analysis of Granger Causality Studies
Entropy, 2023 Granger causality provides a framework that uses predictability to identify causation between time series variables. This is important to policymakers for effective policy management and recommendations.
Weng Siew Lam +3 more
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Sparse Granger Causality Analysis Model Based on Sensors Correlation for Emotion Recognition Classification in Electroencephalography [PDF]
Frontiers in Computational Neuroscience, 2021 In recent years, affective computing based on electroencephalogram (EEG) data has attracted increased attention. As a classic EEG feature extraction model, Granger causality analysis has been widely used in emotion classification models, which construct ...
Dongwei Chen +5 more
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Description Length Guided Unified Granger Causality Analysis [PDF]
IEEE Access, 2021 In this article, we propose a description length guided unified Granger causality analysis (uGCA) framework for sequential medical imaging. While existing efforts of GCA focused on causal relation design and statistical methods for their improvement, our
Zhenghui Hu +3 more
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Granger causality analysis in neuroscience and neuroimaging. [PDF]
J Neurosci, 2015 ### Introduction A key challenge in neuroscience and, in particular, neuroimaging, is to move beyond identification of regional activations toward the characterization of functional circuits underpinning perception, cognition, behavior, and consciousness.
Seth AK, Barrett AB, Barnett L.
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Video Sensor-Based Complex Scene Analysis with Granger Causality [PDF]
Sensors, 2013 In this report, we propose a novel framework to explore the activity interactions and temporal dependencies between activities in complex video surveillance scenes.
Shuang Wu +4 more
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Multivariate Timing and Granger Causality Analysis of Spontaneous Facial Mimicry in Response to Android Dynamic Facial Expressions [PDF]
SensorsAlthough evidence exists for android-induced spontaneous facial mimicry, the timing and temporal precedence (Granger causality) of this effect remain uncertain.
Chun-Ting Hsu +4 more
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Robust unified Granger causality analysis: a normalized maximum likelihood form [PDF]
Brain Informatics, 2021 Unified Granger causality analysis (uGCA) alters conventional two-stage Granger causality analysis into a unified code-length guided framework. We have presented several forms of uGCA methods to investigate causal connectivities, and different forms of ...
Zhenghui Hu +5 more
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