Some Thoughts on Symbolic Transfer Entropy
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866929509912018944 |
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| author | Jin, Dian |
| author_facet | Jin, Dian |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_14745 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Some Thoughts on Symbolic Transfer Entropy Jin, Dian Computational Complexity Information Theory 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. |
| title | Some Thoughts on Symbolic Transfer Entropy |
| topic | Computational Complexity Information Theory |
| url | https://arxiv.org/abs/2409.14745 |