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BROJA-2PID: A Robust Estimator for Bivariate Partial Information Decomposition

Institute of Computer Science, University of Tartu, Ülikooli 17, 51014 Tartu, Estonia
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Entropy 2018, 20(4), 271;
Received: 22 February 2018 / Revised: 27 March 2018 / Accepted: 9 April 2018 / Published: 11 April 2018
(This article belongs to the Section Information Theory, Probability and Statistics)
Makkeh, Theis, and Vicente found that Cone Programming model is the most robust to compute the Bertschinger et al. partial information decomposition (BROJA PID) measure. We developed a production-quality robust software that computes the BROJA PID measure based on the Cone Programming model. In this paper, we prove the important property of strong duality for the Cone Program and prove an equivalence between the Cone Program and the original Convex problem. Then, we describe in detail our software, explain how to use it, and perform some experiments comparing it to other estimators. Finally, we show that the software can be extended to compute some quantities of a trivaraite PID measure. View Full-Text
Keywords: bivariate information decomposition; Cone Programming bivariate information decomposition; Cone Programming
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Makkeh, A.; Theis, D.O.; Vicente, R. BROJA-2PID: A Robust Estimator for Bivariate Partial Information Decomposition. Entropy 2018, 20, 271.

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