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MAXENT3D_PID: An Estimator for the Maximum-entropy Trivariate Partial Information Decomposition
- Source :
- Entropy 21 (9), 862, 2019
- Publication Year :
- 2019
-
Abstract
- Chicharro (2017) introduced a procedure to determine multivariate partial information measures within the maximum entropy framework, separating unique, redundant, and synergistic components of information. Makkeh, Theis, and Vicente (2018) formulated the latter trivariate partial information measure as Cone Programming. In this paper, we present MAXENT3D_PID, a production-quality software that computes the trivariate partial information measure based on the Cone Programming model. We describe in detail our software, explain how to use it, and perform some experiments reflecting its accuracy in estimating the trivariate partial information decomposition.
- Subjects :
- Statistics - Computation
Mathematics - Optimization and Control
Subjects
Details
- Database :
- arXiv
- Journal :
- Entropy 21 (9), 862, 2019
- Publication Type :
- Report
- Accession number :
- edsarx.1901.03352
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.3390/e21090862