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dc.rights.licenseopenen_US
hal.structure.identifierGroupe de Recherche en Economie Théorique et Appliquée [GREThA]
dc.contributor.authorVAN DER POL, Johannes
IDREF: 201468263
dc.date.accessioned2020-02-20T20:01:50Z
dc.date.available2020-02-20T20:01:50Z
dc.date.issued2018
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/3641
dc.description.abstractEnExponential family random graph models (ERGM) are increasingly used in the study of social networks. These models are build to explain the global structure of a network while allowing inference on tie prediction on a micro level. The number of papers within economics is however limited. Possible applications for economics are however abundant. The aim of this document is to provide an explanation of the basic mechanics behind the models and provide a sample code (using R and the packages statnet and ERGM) to operationalize and interpret results and analyse goodness of fit. After reading this paper the reader should be able to start their own analysis.
dc.language.isoENen_US
dc.subject.enNetworks
dc.subject.enExponential random graph model (ERGM)
dc.subject.enInnovation networks
dc.subject.enp-Star (p*)
dc.subject.enStatnet
dc.subject.enTie formation
dc.title.enIntroduction to Network Modeling Using Exponential Random Graph Models (ERGM): Theory and an Application Using R-Project
dc.typeArticle de revueen_US
dc.identifier.doi10.1007/s10614-018-9853-2en_US
dc.subject.halÉconomie et finance quantitative [q-fin]en_US
bordeaux.journalComputational Economicsen_US
bordeaux.pagepp.845-875en_US
bordeaux.volume54en_US
bordeaux.hal.laboratoriesGroupe de Recherche en Economie Théorique et Appliquée (GREThA) - UMR 5113en_US
bordeaux.issue3en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-02486328
hal.version1
hal.date.transferred2020-02-20T20:01:53Z
hal.exporttrue
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