Spectral causalities are now widely used in physical and biological sciences to characterize directional couplings from time series. In particular, the Granger-Geweke spectrum is a frequency decomposition of a Wiener-Granger causality measure. However, there are considerable difficulties in their interpretation, so quite hot debates still arise. Here, the problem is studied within the dynamical effects framework: spectral effects are introduced as long-term effects of relevant parameter interventions. Quantitative relationships between the GG spectrum and certain spectral effects are established for linear stochastic differential equations. It is also argued that in general existing spectral causalities do not unambiguously relate to spectr...
Background: Quantifying interactions among many neurons is fundamental to understanding system-level...
The concept of causality has been widely studied in econometrics and statistics since 1969, when C. ...
We develop a general dynamical model as a framework for possible causal interpretation. We first sta...
Spectral measures of causality are used to explore the role of different rhythms in the causal conne...
A widely agreed upon definition of time series causality inference, established in the sem-inal 1969...
Telling a cause from its effect using observed time series data is a major challenge in natural and ...
Experiments in many fields of science and engineering yield data in the form of time series. The Fou...
Experiments in many fields of science and engineering yield data in the form of time series. The Fou...
AbstractThis technical paper offers a critical re-evaluation of (spectral) Granger causality measure...
We develop a bivariate spectral Granger-causality test that can be applied at each individual freque...
Assessing Granger causality (GC) intended as the influence, in terms of reduction of variance of sur...
Granger-causality is a popular definition of causality that permits a statistical test to determine ...
textabstractWe develop a bivariate spectral Granger-causality test that can be applied at each indiv...
This article proposes a systematic methodological review and an objective criticism of existing meth...
Assessing Granger causality (GC) intended as the influence, in terms of reduction of variance of sur...
Background: Quantifying interactions among many neurons is fundamental to understanding system-level...
The concept of causality has been widely studied in econometrics and statistics since 1969, when C. ...
We develop a general dynamical model as a framework for possible causal interpretation. We first sta...
Spectral measures of causality are used to explore the role of different rhythms in the causal conne...
A widely agreed upon definition of time series causality inference, established in the sem-inal 1969...
Telling a cause from its effect using observed time series data is a major challenge in natural and ...
Experiments in many fields of science and engineering yield data in the form of time series. The Fou...
Experiments in many fields of science and engineering yield data in the form of time series. The Fou...
AbstractThis technical paper offers a critical re-evaluation of (spectral) Granger causality measure...
We develop a bivariate spectral Granger-causality test that can be applied at each individual freque...
Assessing Granger causality (GC) intended as the influence, in terms of reduction of variance of sur...
Granger-causality is a popular definition of causality that permits a statistical test to determine ...
textabstractWe develop a bivariate spectral Granger-causality test that can be applied at each indiv...
This article proposes a systematic methodological review and an objective criticism of existing meth...
Assessing Granger causality (GC) intended as the influence, in terms of reduction of variance of sur...
Background: Quantifying interactions among many neurons is fundamental to understanding system-level...
The concept of causality has been widely studied in econometrics and statistics since 1969, when C. ...
We develop a general dynamical model as a framework for possible causal interpretation. We first sta...