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Correntropy based Granger causality

by Il Park, Jose ́ C. Prı́ncipe - IEEE International Conference on Acoustics, Speech and Signal Processing , 2008
"... We propose a novel nonlinear extension to Granger causality. It is derived from a nonlinear mapping of a stochastic process using the recently introduced generalized correlation measure called correntropy. The method is demonstrated by detecting the direction of coupling in a chaotic system where th ..."
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We propose a novel nonlinear extension to Granger causality. It is derived from a nonlinear mapping of a stochastic process using the recently introduced generalized correlation measure called correntropy. The method is demonstrated by detecting the direction of coupling in a chaotic system where

multi-step Granger causality

by Chao-yi Dong, Dongkwan Shin, Sunghoon Joo, Yoonkey Nam
"... Motivation: Feedback circuits are crucial network motifs, ubiquitously found in many intra- and inter-cellular regulatory networks, and also act as basic building blocks for inducing synchronized bursting behaviors in neural network dynamics. Therefore, the system-level identification of feedback ci ..."
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. Based on multivariate time-series analysis, MSGCM used a modified Wald test to infer the existence of multi-step Granger causality between a pair of network nodes. A significant bi-directional multi-step Granger causality between two nodes indicated the existence of a feedback

Surrogate-Based Test for Granger Causality

by Temujin Gautama, Marc M. Van Hulle - in: Proceedings IEEE Neural Network for Signal Processing Workshop , 2003
"... A novel approach for testing the presence of Granger causality between two time series is proposed. The residue of the destination signal after self-prediction is computed, after which a crossprediction of the source signal over this residue is examined. In the absence of causality, there should be ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
A novel approach for testing the presence of Granger causality between two time series is proposed. The residue of the destination signal after self-prediction is computed, after which a crossprediction of the source signal over this residue is examined. In the absence of causality, there should

An Out of Sample Test for Granger Causality

by John Chao, Valentina Corradi, Norman Swanson - Macroeconomic Dynamics , 2000
"... Granger (1980) summarizes his personal viewpoint on testing for causality, and outlines what he considers to be a useful operational version of his original denition of causality (Granger (1969)), which he notes was partially alluded to in Wiener (1958). This operational version is based on a compar ..."
Abstract - Cited by 17 (7 self) - Add to MetaCart
Granger (1980) summarizes his personal viewpoint on testing for causality, and outlines what he considers to be a useful operational version of his original denition of causality (Granger (1969)), which he notes was partially alluded to in Wiener (1958). This operational version is based on a

Temporal Causal Modeling with Graphical Granger Methods

by Andrew Arnold, Yan Liu, Naoki Abe - In Proceedings of the 13th Int. Conference on Knowledge Discovery and Data Mining, 66 – 75: Association for Computing Machinery , 2007
"... The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data, which raises the challenge of how best to leverage the temporal information for causal modeling. Recently graphical mod ..."
Abstract - Cited by 41 (6 self) - Add to MetaCart
modeling with the concept of “Granger causality”, based on the intuition that a cause helps predict its effects in the future, has gained attention in many domains involving time series data analysis. With the surge of interest in model selection methodologies for regression, such as the Lasso

Testing for Granger Non-causality in Heterogeneous Panels

by Christophe Hurlin , 2007
"... This paper proposes a very simple test of Granger (1969) non-causality for heterogeneous panel data models. Our test statistic is based on the individual Wald statistics of Granger non causality averaged across the groups. First, this statistic is shown to converge sequentially to a standard normal ..."
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This paper proposes a very simple test of Granger (1969) non-causality for heterogeneous panel data models. Our test statistic is based on the individual Wald statistics of Granger non causality averaged across the groups. First, this statistic is shown to converge sequentially to a standard normal

Testing for Granger Non-causality in Heterogeneous Panels

by Elena-ivona Dumitrescu, Christophe Hurlin , 2012
"... This paper proposes a very simple test of Granger (1969) non-causality for heterogeneous panel data models. Our test statistic is based on the individual Wald statistics of Granger non causality averaged across the cross-section units. First, this statistic is shown to converge sequentially to a sta ..."
Abstract - Cited by 8 (0 self) - Add to MetaCart
This paper proposes a very simple test of Granger (1969) non-causality for heterogeneous panel data models. Our test statistic is based on the individual Wald statistics of Granger non causality averaged across the cross-section units. First, this statistic is shown to converge sequentially to a

The distortionary effects of temporal aggregation on granger causality

by Rajaguru Gulasekaran, Tilak Abeysinghe, Rajaguru Gulasekaran, Tilak Abeysinghe, Correspondence Tilak Abeysinghe , 2002
"... Abstract: Economists often have to use temporally aggregated data in causality tests. A number of theoretical studies have pointed out that temporal aggregation has distorting effects on causal inference. This paper provides a quantitative assessment of the magnitude of the distortions created by te ..."
Abstract - Cited by 6 (4 self) - Add to MetaCart
levels of temporal aggregation. At high levels of aggregation, causal information concentrates in contemporaneous correlations. At present, a data-based approach is not available to establish the direction of causality between contemporaneously correlated variables.

Kernelizing Geweke’s Measure of Granger Causality

by P. O. Amblard, R. Vincent, O. J. J. Michel, C. Richard - In Proceedings of the IEEE Workshop on MLSP , 2012
"... In this paper we extend Geweke’s approach of Granger causality by deriving a nonlinear framework based on functional regression in reproducing kernel Hilbert spaces (RKHS). After giving the definitions of dynamical and instantaneous causality in the Granger sense, we review Geweke’s measures. These ..."
Abstract - Cited by 3 (2 self) - Add to MetaCart
In this paper we extend Geweke’s approach of Granger causality by deriving a nonlinear framework based on functional regression in reproducing kernel Hilbert spaces (RKHS). After giving the definitions of dynamical and instantaneous causality in the Granger sense, we review Geweke’s measures

No.7 The Granger Non-Causality Test in

by Cointegrated Vector Autoregressions, Hiroaki Chigira, Taku Yamamoto , 2003
"... In general, Wald tests for the Granger non-causality in vector autoregressive(VAR) process are known to have non-standard asymptotic properties for cointegrated systems. However, that may have standard asymptotic properties depending on the rank of the sub-matrix of cointegration. In this paper, we ..."
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propose a procedure for conducting Granger non-causality tests that are based on discrimination of these asymptotic properties. This paper also investigate the finite sample performance of our testing procedure, and com-pare the testing procedure with conventional causality tests in levels VAR’s. 1
Results 1 - 10 of 390