期刊
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS
卷 57, 期 -, 页码 329-341出版社
WILEY
DOI: 10.1111/j.1467-9876.2007.00616.x
关键词
Bayes's theorem; evaluation of evidence; forensic science; handwriting evidence; likelihood ratio; multivariate data
The evaluation of handwritten characters that are selected from an anonymous letter and written material from a suspect is an open problem in forensic science. The individualization of handwriting is largely dependent on examiners who evaluate the characteristics in a qualitative and subjective way. Precise individual characterization of the shape of handwritten characters is possible through Fourier analysis: each handwritten character can be described through a set of variables such as the surface and harmonics as demonstrated by Marquis and co-workers in 2005. The assessment of the value of the evidence is performed through the derivation of a likelihood ratio for multivariate data. The methodology allows the forensic scientist to take into account the correlation between variables, and the non-constant variability within sources (i.e. individuals). Numerical procedures are implemented to handle the complexity and to compute the marginal likelihood under competing propositions.
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