Granger causality with signal-dependent noise
Luo, Qiang, Ge, Tian and Feng, Jianfeng. (2011) Granger causality with signal-dependent noise. Neuroimage, Vol.57 (No.4). pp. 1422-1429. ISSN 1053-8119Full text not available from this repository.
Official URL: http://dx.doi.org/10.1016/j.neuroimage.2011.05.054
It is generally believed that the noise variance in in vivo neuronal data exhibits time-varying volatility, particularly signal-dependent noise. Despite a widely used and powerful tool to detect causal influences in various data sources, Granger causality has not been well tailored for time-varying volatility models. In this technical note, a unified treatment of the causal influences in both mean and variance is naturally proposed on models with signal-dependent noise in both time and frequency domains. The approach is first systematically validated on toy models, and then applied to the physiological data collected from Parkinson patients, where a clear advantage over the classical Granger causality is demonstrated.
|Item Type:||Journal Article|
|Subjects:||Q Science > QA Mathematics
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
T Technology > TK Electrical engineering. Electronics Nuclear engineering
|Divisions:||Faculty of Science > Computer Science|
|Library of Congress Subject Headings (LCSH):||Time-series analysis, Statistical hypothesis testing, Signal processing, Parkinson's disease, Brain -- Imaging -- Statistical methods|
|Journal or Publication Title:||Neuroimage|
|Date:||15 August 2011|
|Page Range:||pp. 1422-1429|
|Funder:||Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation of China] (NSFC)|
|Grant number:||60904065 (NSFC), 71031007 (NSFC)|
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