In this work, we propose a new method to compute GC which combines SS and PC and tests it together with other four commonly used estimation approaches.

The results of our simulation show that the bias and variance of the estimates of the multivariate GC strongly depend on the amount of data samples available ...

This work proposes a new method to compute GC which combines SS and PC and tests it together with other four commonly used estimation approaches, ...

Testing different methodologies for Granger causality estimation: A simulation study ; Yuri Antonacci at Università degli Studi di Palermo. Yuri Antonacci.

Testing different methodologies for Granger causality estimation: A simulation study. Y. Antonacci, L. Astolfi, and L. Faes. EUSIPCO, page 940-944. IEEE ...

The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another.

In this paper, we compare two existing approaches in the frequency domain, proposed originally by Pierce (1979) and Geweke (1982), and introduce a new testing ...

If the underlying time series data are non-stationary and cointegrated then the method used for testing causality is Engle and Granger error correction ...

Oct 22, 2021 · We propose three new methods for lag estimation in multivariate time series, based on autoregressive modelling and information theory.

Granger causality has become a popular tool for analyzing time series data in many application domains, from economics and finance to genomics and neuroscience.