Preview

Theory and Practice of Forensic Science

Advanced search

APPLYING BAYESIAN METHODS FOR METROLOGICAL EVALUATION AND INTERPRETATION OF FORENSIC EVIDENCE

Abstract

The paper summarizes Bayesian approaches to uncertainty assessment of forensic
examination results and o#ers a brief overview of current achievements in the application
of the likelihood ratio concept in forensic practice.

About the Authors

G. Bebeshko
Russian Federal Center of Forensic Science of the Russian Ministry of Justice
Russian Federation
Lead Forensic Examiner


S. Voytov
Bryansk Forensic Science Laboratory of the Russian Ministry of Justice
Russian Federation
Forensic Examiner


G. Omelyanyuk
Russian Federal Center of Forensic Science of the Russian Ministry of Justice
Russian Federation
Deputy Director


A. Usov
Russian Federal Center of Forensic Science of the Russian Ministry of Justice
Russian Federation
Deputy Director


References

1. ch. 3 st. 123 Konstitutsii Rossiiskoi Federatsii. (In Russ.)

2. Evett I.W. Expressing evaluative opinions: A position statement // Science and Justice. 2011. Vol. 51. P.1-2. DOI: 10.1016/j.scijus.2011.01.002

3. Berger C.E.H. et al. Evidence evaluation: A response to the Court of Appeal judgment in RvT // Science and Justice. 2011. Vol. 51. P. 43-49

4. Robertson B. et al. Extending the confusion about Bayes // Modern Law Review. 2011. Vol. 74. P. 444-445

5. Redmayne M. et al. Forensic science evidence in question // Criminal Law Review. 2011. Vol. 5. P. 347-356

6. Fenton N. Improve statistics in court // Nature. 2011. Vol. 479, 3 November. P. 36-37

7. Morrison G.S.The likelihood-ratio framework and forensic evidence in court: A response to R v T // International Journal of Evidence and Proof. 2012. Vol. 16. P. 1-29 / DOI: 10.1350/ijep.2012.16.1.390

8. Aitken C.G.G., Taroni F. Statistics and the Evaluation of Evidence for Forensic Scientists, second edition, Wiley, London. 2004. 510 pp.

9. Jeffreys H. Theory of Probability. Oxford University Press, 1983.

10. Morrison G.S. Measuring the validity and reliability of forensic likelihoodratio systems // Science and Justice. 2011. Vol. 51. P. 91-98

11. Ramos D., Gonzalez-Rodriguez J. Reliable support: Measuring calibration of likelihood ratios // Forensic Science International. 2013. Vol. 230. № 1-3. P. 156-169.

12. Brummer N., du Preez. Application independent evaluation of speaker detection // Computer Speech and Language. 2006. Vol. 20. P. 230-275.

13. Morrison G.S. Likelihood-ratio forensic voice comparison using parametric representations of the formant trajectories of diphthongs // The Journal of the Acoustical Society of America. 2009. Vol. 125. P. 2387-2397.

14. Morrison G.S., Zhang C., Rose P. An empirical estimate of the precision of likelihood-ratios from a forensic-comparison system // Forensic Science International. 2011. Vol. 208. P. 59-65.

15. Foreman L.A. et al. Interpreting DNA evidence: A review // International Statistics Journal. 2003. Vol. 71. P. 473-495.

16. Hepler A.B. et al. Score-based likelihood for handwriting evidence // Forensic Science International. 2012. Vol. 219. P. 129-140.

17. Neumann C. et al. Quantifying the weight of evidence from a forensic fingerprint comparison: A new paradigm // Journal of the Royal Statistical Society. 2012. Vol. 175. P. 371-415.

18. Skerrett, J., Neumann, C., Mateos-Garcia, I. A Bayesian approach for interpreting shoemark evidence in forensic casework: Accounting for wear features // Forensic Science International. Vol. 210 (1-3). P. 26-30

19.


Review

For citations:


Bebeshko G., Voytov S., Omelyanyuk G., Usov A. APPLYING BAYESIAN METHODS FOR METROLOGICAL EVALUATION AND INTERPRETATION OF FORENSIC EVIDENCE. Theory and Practice of Forensic Science. 2014;(1(33)):148-158. (In Russ.)

Views: 637


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1819-2785 (Print)
ISSN 2587-7275 (Online)