Introduction

A General Framework for the Estimation of Likelihood Ratios

A General Framework for the Estimation of Likelihood Ratios

Overview

This talk provides a very general framework for the estimation of likelihood ratios using similarity or dissimilarity scores resulting from a comparison of two patterns that overcome this deficiency for suitably chosen similarity measures. In such instances, the likelihood ratio estimate defined is in fact a good approximation for the classical likelihood ratio. Moreover, the quality of the approximation improves with increasing empirical information. This approach can be applied even when the data are numbers, vectors or attributes such as color. This presentation illustrates the approach using examples involving glass fragments, fingerprint comparisons, bullet casing marks and DNA profiles.

Presenter

  • Steve Lund

Funding for this Forensic Technology Center of Excellence webinar has been provided by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice.

The opinions, findings, and conclusions or recommendations expressed in this webinar are those of the presenter(s) and do not necessarily reflect those of the U.S. Department of Justice.

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