Analysis of Sampling Issues Using Bayesian Networks

Posted: 7 Jul 2008

See all articles by Alex Biedermann

Alex Biedermann

University of Lausanne

F. Taroni

Independent

S. Bozza

Ca Foscari University of Venice - Dipartimento di Economia

C. G. G. Aitken

University of Edinburgh - School of Mathematics

Date Written: March 2008

Abstract

This paper addresses the implementation of Bayesian sampling methodology in a graphical probability environment, i.e. Bayesian networks (BNs). An architecture of BNs which is able to be used for sampling from small and large consignments is outlined in detail. Through direct interaction with their users, the proposed models provide a framework that is capable of dealing with several distinct sampling issues, such as (i) the calculation of posterior probability distributions for the proportion of ‘positives’ (i.e. discrete units with a characteristic of interest) in a consignment as well as for the number of positives among a consignment's uninspected items, (ii) case preassessment and (iii) likelihood-ratio evaluation. A discussion is included on features of the proposed models that allow one to account for further complications such as competing prior beliefs about the proportion of positives in a consignment and potentially misclassified data (e.g. positive testing results obtained from units that are actually negative).

Keywords: sampling, forensic science, Bayesian networks, likelihood ratio, Bayes', theorem, preassessment, evidence evaluation

Suggested Citation

Biedermann, Alex and Taroni, F. and Bozza, S. and Aitken, C. G. G., Analysis of Sampling Issues Using Bayesian Networks (March 2008). Law, Probability & Risk, Vol. 7, Issue 1, pp. 35-60, 2008, Available at SSRN: https://ssrn.com/abstract=1156218 or http://dx.doi.org/10.1093/lpr/mgm041

Alex Biedermann (Contact Author)

University of Lausanne ( email )

Faculty of Law, Criminal Justice and Public Admin.
Lausanne, Vaud 1015
Switzerland

HOME PAGE: http://www.unil.ch/unisciences/alexbiedermann

F. Taroni

Independent

S. Bozza

Ca Foscari University of Venice - Dipartimento di Economia ( email )

Cannaregio 873
Venice, 30121
Italy

C. G. G. Aitken

University of Edinburgh - School of Mathematics ( email )

United Kingdom
0131 650 4877 (Phone)

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