Paper
25 August 2004 A comparison of statistical methods for evaluating matching performance of a biometric identification device: a preliminary report
Michael E. Schuckers, Anne Hawley, Katie Livingstone, Nona Mramba
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Abstract
Confidence intervals are an important way to assess and estimate a parameter. In the case of biometric identification devices, several approaches to confidence intervals for an error rate have been proposed. Here we evaluate six of these methods. To complete this evaluation, we simulate data from a wide variety of parameter values. This data are simulated via a correlated binary distribution. We then determine how well these methods do at what they say they do: capturing the parameter inside the confidence interval. In addition, the average widths of the various confidence intervals are recorded for each set of parameters. The complete results of this simulation are presented graphically for easy comparison. We conclude by making a recommendation regarding which method performs best.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael E. Schuckers, Anne Hawley, Katie Livingstone, and Nona Mramba "A comparison of statistical methods for evaluating matching performance of a biometric identification device: a preliminary report", Proc. SPIE 5404, Biometric Technology for Human Identification, (25 August 2004); https://doi.org/10.1117/12.541899
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Cited by 14 scholarly publications.
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KEYWORDS
Biometrics

Error analysis

Binary data

Monte Carlo methods

Statistical methods

Statistical analysis

Biological research

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