USING THE BETA-BINOMIAL DISTRIBUTION TO ASSESS PERFORMANCE OF A BIOMETRIC IDENTIFICATION DEVICE

Abstract

This paper discusses the use of the Beta-binomial distribution to estimate the matching performance of a biometric identification device. Specifically, the Beta-binomial distribution can be used to assess the variability in estimates of the false match and the false non-match rates when multiple users are tested more than once. This method accounts for the extraneous variability in this scenario and allows for the creation of confidence intervals under certain regularity conditions. The Beta-binomial differs from the binomial in that it models the extra-variation that is due to a lack of marginal independence among the observations. The Beta-binomial also has the flexibility to model the correlation of observations by the same individual that the binomial does not possess. This paper discusses maximum likelihood methodology for estimating the parameters of the Beta-binomial distribution. Finally, examples are given for simulated data that explicate this methodology.