Modern statistical models for forensic fingerprint examinations: A critical review

作者：Abraham Joshua^*; Champod Christophe; Lennard Chris; Roux Claude

来源：Forensic Science International, 2013, 232(1-3): 131-150.

DOI：10.1016/j.forsciint.2013.07.005

• Statistical models
• Fingerprint modelling
• Fingerprint evidence
• Likelihood Ratios
• Review paper

Over the last decade, the development of statistical models in support of forensic fingerprint identification has been the subject of increasing research attention, spurned on recently by commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. Such models are increasingly seen as useful tools in support of the fingerprint identification process within or in addition to the ACE-V framework. %26lt;br%26gt;This paper provides a critical review of recent statistical models from both a practical and theoretical perspective. This includes analysis of models of two different methodologies: Probability of Random Correspondence (PRC) models that focus on calculating probabilities of the occurrence of fingerprint configurations for a given population, and Likelihood Ratio (LR) models which use analysis of corresponding features of fingerprints to derive a likelihood value representing the evidential weighting for a potential source.

• 出版日期2013-10-10
• 单位司法部司法鉴定科学技术研究所