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Multivariate Entropy Analysis of Network Data
Stockholm University, Faculty of Social Sciences, Department of Statistics.
2016 (English)In: Bulletin of Sociological Methodology, ISSN 0759-1063, E-ISSN 2070-2779, Vol. 129, 45-63 p.Article in journal (Refereed) Published
Abstract [en]

Multigraphs with numerical or qualitative attributes defined on vertices and edges can benefit from systematic methods based on multivariate entropies for describing and analysing the interdependencies that are present between vertex and edge attributes. This is here illustrated by application of these tools to a subset of data on the social relations among Renaissance Florentine families collected by John Padgett. Using multivariate entropies we show how it is possible to systematically check for tendencies in data that can be described as independencies or conditional independencies, or as dependencies allowing certain combinations of variables to predict other variables. We also show how different structural models can be tested by divergence measures obtained from the multivariate entropies.

Place, publisher, year, edition, pages
Sage Publications, 2016. Vol. 129, 45-63 p.
Keyword [en]
Statistical Entropy, Independence, Association, Prediction, Functional Dependence, Divergence Tests, Social Network Analysis
National Category
Probability Theory and Statistics
URN: urn:nbn:se:su:diva-125256DOI: 10.1177/0759106315615511OAI: diva2:892214
Available from: 2016-01-08 Created: 2016-01-08 Last updated: 2016-01-11Bibliographically approved

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Frank, Ove
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