ABSTRACT
An important issue in the investigation of suspect crime is having appropriate standards for interpreting and weighting forensic evidence (Koblentz 2010). In recent years, the state of the art in forensic interpretation has been to evaluate forensic evidence using likelihood ratios in the framework of Bayesian hypothesis testing. In this framework, it is used to evaluate to what extent results from forensic investigation speak in favor of the prosecutors or defendants hypotheses
CONTENTS
20.1 Introduction .......................................................................................................................... 231 20.2 Introduction to Bayesian Networks in Forensics .................................................................. 232
20.2.1 Bayesian Statistics in Forensic Science .................................................................... 232 20.2.2 Introduction to Bayesian Networks .......................................................................... 235
20.3 Applicability to Forensic Entomology .................................................................................. 235 20.4 Constructing the Bayesian Network ..................................................................................... 237
20.4.1 Sources of Data ......................................................................................................... 237 20.4.2 Data for Development Rate of Calliphora vicina ..................................................... 237 20.4.3 Data on Length in Different Intervals ...................................................................... 237 20.4.4 Data to Support Assumptions on Precolonization Time .......................................... 237
20.5 Bayesian Network for Forensic Entomology ........................................................................ 238 20.5.1 Model Structure ........................................................................................................ 238 20.5.2 Calculating Probabilities ..........................................................................................240 20.5.3 Applying the BBN to a Case ..................................................................................... 241
20.5.3.1 Case 1 .........................................................................................................242 20.5.3.2 Case 2 ......................................................................................................... 243 20.5.3.3 Case 3 .........................................................................................................244
20.6 Discussion .............................................................................................................................246 20.7 Limits and Possibilities ......................................................................................................... 247 20.8 Future Prospects ................................................................................................................... 247 Acknowledgments .......................................................................................................................... 247 References ...................................................................................................................................... 247
