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A general model-based causal inference method overcomes the curse of synchrony and indirect effect
To identify causation, model-free inference methods, such as Granger Causality, have been widely used due to their flexibility. However, they have difficulty distinguishing synchrony and indirect effects from direct causation, leading to false predictions. To overcome this, model-based inference met...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366229/ https://www.ncbi.nlm.nih.gov/pubmed/37488136 http://dx.doi.org/10.1038/s41467-023-39983-4 |