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Quantifying redundancies and synergies with measures of inequality
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.ORCID iD: 0000-0001-5524-0552
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Computer Systems.ORCID iD: 0000-0002-1527-734X
2024 (English)In: PLOS ONE, E-ISSN 1932-6203, Vol. 19, no 11, article id e0313281Article in journal (Refereed) Published
Abstract [en]

Inequality measures provide a valuable tool for the analysis, comparison, and optimization based on system models. This work studies the relation between attributes or features of an individual to understand how redundant, unique, and synergetic interactions between attributes construct inequality. For this purpose, we define a family of inequality measures (f-inequality) from f-divergences. Special cases of this family are, among others, the Pietra index and the Generalized Entropy index. We present a decomposition for any f-inequality with intuitive set-theoretic behavior that enables studying the dynamics between attributes. Moreover, we use the Atkinson index as an example to demonstrate how the decomposition can be transformed to measures beyond f-inequality. The presented decomposition provides practical insights for system analyses and complements subgroup decompositions. Additionally, the results present an interesting interpretation of Shapley values and demonstrate the close relation between decomposing measures of inequality and information.

Place, publisher, year, edition, pages
Public Library of Science (PLoS), 2024. Vol. 19, no 11, article id e0313281
National Category
Computer Systems Sociology Economics
Research subject
Applied Mathematics and Statistics
Identifiers
URN: urn:nbn:se:uu:diva-543577DOI: 10.1371/journal.pone.0313281ISI: 001360845400021PubMedID: 39565765Scopus ID: 2-s2.0-85209695452OAI: oai:DiVA.org:uu-543577DiVA, id: diva2:1915237
Projects
Resilient Internet of Things (RIOT)
Funder
Swedish Civil Contingencies Agency, MSB 2018-12526Available from: 2024-11-21 Created: 2024-11-21 Last updated: 2024-12-12Bibliographically approved

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Mages, TobiasRohner, Christian

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