Estimating Conditional Transfer Entropy in Time Series Using Mutual Information and Nonlinear Prediction

We propose a new estimator to measure directed dependencies in time series. The dimensionality of data is first reduced using a new non-uniform embedding technique, where the variables are ranked according to a weighted sum of the amount of new information and improvement of the prediction accuracy...

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Detalles Bibliográficos
Autores principales: Shahsavari Baboukani, Payam, Graversen, Carina, Alickovic, Emina, Østergaard, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597255/
https://www.ncbi.nlm.nih.gov/pubmed/33286893
http://dx.doi.org/10.3390/e22101124

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597255/
https://www.ncbi.nlm.nih.gov/pubmed/33286893
http://dx.doi.org/10.3390/e22101124

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