Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/56628 
Year of Publication: 
2011
Series/Report no.: 
SFB 649 Discussion Paper No. 2011-045
Publisher: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
Abstract: 
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.
Subjects: 
Bayesian Networks
structure learning
offender profiling
JEL: 
C49
C81
K42
Document Type: 
Working Paper

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