Bayesian Networks and sex-related homicides

We 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.

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Year of publication:	2011
Authors:	Stahlschmidt, Stephan ; Tausendteufel, Helmut ; Härdle, Wolfgang Karl
Publisher:	Berlin : Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
Subject:	Gewalt \| Sexuelle Belästigung \| Bayes-Statistik \| Bayesian Networks \| structure learning \| offender profiling

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Series:	SFB 649 Discussion Paper ; 2011-045
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	667236740 [GVK] hdl:10419/56628 [Handle] RePEc:zbw:sfb649:sfb649dp2011-045 [RePEc]
Classification:	C49 - Econometric and Statistical Methods: Special Topics. Other ; C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data ; K42 - Illegal Behavior and the Enforcement of Law
Source:	EconStor

Persistent link: https://www.econbiz.de/10010281482