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Bayesian Dynamical Systems Modelling in the Social Sciences

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dc.contributor.authorRanganathan, Shyamen
dc.contributor.authorSpaiser, Viktoriaen
dc.contributor.authorMann, Richard P.en
dc.contributor.authorSumpter, David J. T.en
dc.contributor.departmentStatisticsen
dc.date.accessioned2018-02-21T21:25:54Zen
dc.date.available2018-02-21T21:25:54Zen
dc.date.issued2014-01-20en
dc.description.abstractData arising from social systems is often highly complex, involving non-linear relationships between the macro-level variables that characterize these systems. We present a method for analyzing this type of longitudinal or panel data using differential equations. We identify the best non-linear functions that capture interactions between variables, employing Bayes factor to decide how many interaction terms should be included in the model. This method punishes overly complicated models and identifies models with the most explanatory power. We illustrate our approach on the classic example of relating democracy and economic growth, identifying non-linear relationships between these two variables. We show how multiple variables and variable lags can be accounted for and provide a toolbox in R to implement our approach.en
dc.description.versionPublished versionen
dc.format.extent? - ? (9) page(s)en
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0086468en
dc.identifier.issn1932-6203en
dc.identifier.issue1en
dc.identifier.orcidRanganathan, S [0000-0002-1337-5173]en
dc.identifier.urihttp://hdl.handle.net/10919/82231en
dc.identifier.volume9en
dc.languageEnglishen
dc.publisherPLOSen
dc.relation.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000330240500135&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=930d57c9ac61a043676db62af60056c1en
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectdiffusionen
dc.subjectdemocracyen
dc.titleBayesian Dynamical Systems Modelling in the Social Sciencesen
dc.title.serialPLOS ONEen
dc.typeArticle - Refereeden
dc.type.otherArticleen
dc.type.otherJournalen
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Scienceen
pubs.organisational-group/Virginia Tech/Science/COS T&R Facultyen
pubs.organisational-group/Virginia Tech/Science/Statisticsen

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