Large Sample Properties of a U-Statistic Comparison for Biometric Individuality

Thomas M. Menino Convention & Exhibition Center 

A common question when deciding whether to consider a type of forensic evidence is the degree at which trace objects from different sources can be distinguished. The degree is referred to as the individuality of the forensic modality, with respect to a specified metric for comparing a large number of samples from multiple sources. Regardless of the sample size, if the metric does not give rise to an exclusionary difference between two sources, then two sources are said to have indistinguishable profiles, with respect to the metric. We use the score developed in Davis et al. (2012) for sparse categorical data arising from the FlashID system©. We will define a new level alpha test for the equality of scores, based on all pairwise comparisons within and between documents from two different writers. In this presentation, we will derive the limiting distribution of our statistic. This test compares average within-writer scores with the between-writer scores. Using the corresponding p-values between all pairs of writers, we use a mixture model to make a statement about the confidence that a given p-value arose from two writers with indistinguishable profiles.

Biometric Individuality

Parametric Bootstrap

U-Statistics

Pairwise Scores 

Section on Nonparametric Statistics