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Bayesian Networks and sex-related homicides

Stephan Stahlschmidt, Helmut Tausendteufel and Wolfgang Härdle

No 2011-045, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

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.

Keywords: Bayesian Networks; structure learning; offender profiling (search for similar items in EconPapers)
JEL-codes: C49 C81 K42 (search for similar items in EconPapers)
Date: 2011
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