Bayesian Networks and the Value of the Evidence for the Forensic Two-Trace Transfer Problem
Détails
ID Serval
serval:BIB_E9ED1D06E495
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Bayesian Networks and the Value of the Evidence for the Forensic Two-Trace Transfer Problem
Périodique
Journal of Forensic Sciences
ISSN
1556-4029 ; 0022-1198
ISSN-L
0022-1198
Statut éditorial
Publié
Date de publication
09/2012
Peer-reviewed
Oui
Volume
57
Numéro
5
Pages
1199-1216
Langue
anglais
Résumé
Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.
Mots-clé
forensic science evaluation of transfer evidence Bayesian networks two-trace problem likelihood ratio graphical probability models object-oriented Bayesian networks
Pubmed
Création de la notice
07/09/2012 12:04
Dernière modification de la notice
20/08/2019 16:12