MAXENT3D_PID: An Estimator for the Maximum-entropy Trivariate Partial Information Decomposition

Abdullah Makkeh, Daniel Chicharro, Dirk Oliver Theis, Raul Vicente
1/10/2019
stat.COmath.OC

Official code: Abzinger/MAXENT3D_PID (3 stars, Apache-2.0, last commit 2021-11-15).

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.

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Code Implementations(1)

Abzinger/MAXENT3D_PIDOfficial100%
Apache-2.0

A Trivariate Partial Information Decomposition Estimator

30PythonJun 21, 20184 years agoApache-2.0

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Cite this paper

@article{makkeh2019maxentdpid,
  title  = {MAXENT3D_PID: An Estimator for the Maximum-entropy Trivariate Partial Information Decomposition},
  author = {Abdullah Makkeh and Daniel Chicharro and Dirk Oliver Theis and Raul Vicente},
  year   = {2019},
  eprint = {1901.03352},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1901.03352}
}

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