Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/56628 
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dc.contributor.authorStahlschmidt, Stephanen
dc.contributor.authorTausendteufel, Helmuten
dc.contributor.authorHärdle, Wolfgang Karlen
dc.date.accessioned2011-08-29-
dc.date.accessioned2012-04-05T16:12:16Z-
dc.date.available2012-04-05T16:12:16Z-
dc.date.issued2011-
dc.identifier.urihttp://hdl.handle.net/10419/56628-
dc.description.abstractWe present a statistical investigation on the domain of sex-related homicides. As general sociological and psychological theory on this specific type of crime is incomplete or even lacking, a data-driven approach is implemented. In detail, graphical modelling is applied to learn the dependency structure and several structure learning algorithms are combined to yield a skeleton corresponding to distinct Bayesian Networks. This graph is subsequently analysed and presents a distinction between an offender and a situation driven crime.en
dc.language.isoengen
dc.publisher|aHumboldt University of Berlin, Collaborative Research Center 649 - Economic Risk |cBerlinen
dc.relation.ispartofseries|aSFB 649 Discussion Paper |x2011-045en
dc.subject.jelC49en
dc.subject.jelC81en
dc.subject.jelK42en
dc.subject.ddc330en
dc.subject.keywordBayesian Networksen
dc.subject.keywordstructure learningen
dc.subject.keywordoffender profilingen
dc.subject.stwGewalten
dc.subject.stwSexuelle Belästigungen
dc.subject.stwBayes-Statistiken
dc.titleBayesian Networks and sex-related homicides-
dc.typeWorking Paperen
dc.identifier.ppn667236740en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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