Results 11 to 20 of about 90,737 (348)
Multiscale Granger causality [PDF]
Physical Review E, 2017 In the study of complex physical and biological systems represented by multivariate stochastic processes, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales.
Faes, Luca +3 more
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Multivariate Granger Causality and Generalized Variance [PDF]
Physical Review E, 2010 Granger causality analysis is a popular method for inference on directed interactions in complex systems of many variables. A shortcoming of the standard framework for Granger causality is that it only allows for examination of interactions between ...
Adam B. Barrett +11 more
core +5 more sources
Neural Granger Causality. [PDF]
IEEE Trans Pattern Anal Mach Intell, 2022 While most classical approaches to Granger causality detection assume linear dynamics, many interactions in real-world applications, like neuroscience and genomics, are inherently nonlinear. In these cases, using linear models may lead to inconsistent estimation of Granger causal interactions.
Tank A +4 more
europepmc +5 more sources
Physical Review E, 2021 Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. For Gaussian variables it is equivalent to transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes.
Sebastiano Stramaglia +3 more
openaire +6 more sources
Granger-causality in Markov switching models [PDF]
SSRN Electronic Journal, 2015 In this paper we propose a new parametrisation of transition probabilities that allows us to characterize and test Granger-causality in Markov switching models by means of an appropriate specification of the transition matrix. Test for independence are also provided. We illustrate our methodology with an empirical application.
Monica Billio, Silvio Di Sanzo
openalex +5 more sources
Measuring Granger Causality in Quantiles [PDF]
Journal of Business & Economic Statistics, 2020 We consider measures of Granger causality in quantiles, which detect and quantify both linear and nonlinear causal effects between random variables. The measures are based on nonparametric quantile regressions and defined as logarithmic functions of restricted and unrestricted expectations of quantile check loss functions.
Song, X., Taamouti, A.
openaire +3 more sources
The relationships between ASEAN stock markets: A spectral Granger causality approach
Tạp chí Khoa học Đại học Mở Thành phố Hồ Chí Minh - Kinh tế và Quản trị kinh doanh, 2021 This article collects data of ASEAN6’s daily stock returns to investigate the relationships among them by traditional Granger causality test in combination with spectral Granger causality test.
Trần Thị Tuấn Anh
doaj +1 more source
Analyzing Multiple Nonlinear Time Series with Extended Granger Causality [PDF]
, 2004 Identifying causal relations among simultaneously acquired signals is an important problem in multivariate time series analysis. For linear stochastic systems Granger proposed a simple procedure called the Granger causality to detect such relations.
Arnhold +28 more
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NeuroImage, 2014 This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality.
Friston, Karl J. +5 more
openaire +4 more sources
Meta-Granger Causality Testing [PDF]
SSRN Electronic Journal, 2015 Understanding the (causal) mechanisms at work is important for formulating evidence-based policy. But evidence from observational studies is often inconclusive with many studies finding conflicting results. In small to moderately sized samples, the outcome of Granger causality testing heavily depends on the lag length chosen for the underlying vector ...
Stephan B. Bruns, David I. Stern
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