Year: 2024
Type: preprint
Abstract: Transfer entropy is used to establish a measure of causal relationships between two variables. Symbolic transfer entropy, as an estimation method for transfer entropy, is widely applied due to its robustness against non-stationarity. This paper investigates the embedding dimension parameter in symbolic transfer entropy and proposes optimization methods for high complexity in extreme cases with complex data. Additionally, it offers some perspectives on estimation methods for transfer entropy.
Source: arXiv (Cornell University)
Author: Jin, Dian
Institution: Hong Kong Polytechnic University
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4403780286