Taking peak area information into account when analysing STR DNA mixtures is acknowledged to be a difficult task. There have been a number of non-probabilistic approaches proposed in the literature, and some have been incorporated into computer systems, but comparatively little has been published from a probabilistic perspective. Here we briefly review our previous work on using Bayesian networks to analyse two-person mixtures within a probabilistic framework, and present preliminary results obtained for analysing two-person and three-person mixtures that combine peak area information from multiple independent samples. © 2008 Elsevier Ireland Ltd. All rights reserved
We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic iden...
This thesis proposes and discusses a statistical model for interpreting forensic DNA mixtures. We de...
We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic ide...
An interesting and complex problem which can readily be handledby using a Bayesian network (BN) is t...
An interesting and complex problem which can readily be handledby using a Bayesian network (BN) is t...
This paper presents a coherent probabilistic framework for taking account of allelic dropout, stu...
This paper presents a coherent probabilistic framework for taking account of allelic dropout, stu...
This paper presents a coherent probabilistic framework for taking account of allelic dropout, stutte...
This paper presents a coherent probabilistic framework for taking account of allelic dropout, stutte...
We present methods for inference about relationships between contributors to a DNA mixture and other...
We present methods for inference about relationships between contributors to a DNA mixture and other...
We show how probabilistic expert systems can be used to analyse forensic identification problems inv...
Statistical analysis of DNA mixtures is known to pose computational challenges due to the enormous s...
We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic ide...
We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic ide...
We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic iden...
This thesis proposes and discusses a statistical model for interpreting forensic DNA mixtures. We de...
We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic ide...
An interesting and complex problem which can readily be handledby using a Bayesian network (BN) is t...
An interesting and complex problem which can readily be handledby using a Bayesian network (BN) is t...
This paper presents a coherent probabilistic framework for taking account of allelic dropout, stu...
This paper presents a coherent probabilistic framework for taking account of allelic dropout, stu...
This paper presents a coherent probabilistic framework for taking account of allelic dropout, stutte...
This paper presents a coherent probabilistic framework for taking account of allelic dropout, stutte...
We present methods for inference about relationships between contributors to a DNA mixture and other...
We present methods for inference about relationships between contributors to a DNA mixture and other...
We show how probabilistic expert systems can be used to analyse forensic identification problems inv...
Statistical analysis of DNA mixtures is known to pose computational challenges due to the enormous s...
We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic ide...
We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic ide...
We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic iden...
This thesis proposes and discusses a statistical model for interpreting forensic DNA mixtures. We de...
We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic ide...