Transfer Entropy for Nonparametric Granger Causality Detection: An Evaluation of Different Resampling Methods
The information-theoretical concept transfer entropy is an ideal measure for detecting conditional independence, or Granger causality in a time series setting. The recent literature indeed witnesses an increased interest in applications of entropy-based tests in this direction. However, those tests...
Main Authors: | Cees Diks, Hao Fang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2017-07-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/19/7/372 |
Similar Items
-
A Consistent Nonparametric Test for Granger Non-Causality Based on the Transfer Entropy
by: Cees Diks, et al.
Published: (2020-10-01) -
The Relation between Granger Causality and Directed Information Theory: A Review
by: Pierre-Olivier Amblard, et al.
Published: (2012-12-01) -
Designing Bivariate Auto-Regressive Timeseries with Controlled Granger Causality
by: Shohei Hidaka, et al.
Published: (2021-06-01) -
A review of the Granger-causality fallacy
by: Mariusz Maziarz
Published: (2015-05-01) -
Multivariate Conditional Granger Causality Analysis for Lagged Response of Soil Respiration in a Temperate Forest
by: Peter S. Curtis, et al.
Published: (2013-10-01)