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

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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Bibliographic Details
Main Authors: Payam Shahsavari Baboukani, Carina Graversen, Emina Alickovic, Jan Østergaard
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Entropy
Subjects:
directed dependency
conditional transfer entropy
non-uniform embedding
nonlinear prediction
mutual information
Online Access:https://www.mdpi.com/1099-4300/22/10/1124

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