Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/56628
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dc.contributor.authorStahlschmidt, Stephanen_US
dc.contributor.authorTausendteufel, Helmuten_US
dc.contributor.authorHärdle, Wolfgang K.en_US
dc.date.accessioned2011-08-29en_US
dc.date.accessioned2012-04-05T16:12:16Z-
dc.date.available2012-04-05T16:12:16Z-
dc.date.issued2011en_US
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_US
dc.language.isoengen_US
dc.publisher|aSFB 649, Economic Risk |cBerlinen_US
dc.relation.ispartofseries|aSFB 649 discussion paper |x2011-045en_US
dc.subject.jelC49en_US
dc.subject.jelC81en_US
dc.subject.jelK42en_US
dc.subject.ddc330en_US
dc.subject.keywordBayesian Networksen_US
dc.subject.keywordstructure learningen_US
dc.subject.keywordoffender profilingen_US
dc.subject.stwGewalten_US
dc.subject.stwSexuelle Belästigungen_US
dc.subject.stwBayes-Statistiken_US
dc.titleBayesian Networks and sex-related homicidesen_US
dc.typeWorking Paperen_US
dc.identifier.ppn667236740en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US

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