Forensic Statistics
Multivariate trace comparison
J.L.F. Göbbels (TU Delft - Electrical Engineering, Mathematics and Computer Science)
J. Söhl – Mentor (TU Delft - Statistics)
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Abstract
In today’s complex, modern world, where more data and knowledge is available then ever before, consensus over approaches in statistics is far away. To understand what this means for forensic statistics, both the frequentist and Bayesian approach are considered in quantifying evidence. Classical frequentist approaches are elaborated according to an example of knife data, where both univariate and multivariate approaches are applied. As an alternative to the previous methods, the likelihood ratio is introduced. To arrive at a unified framework for calculating likelihood ratios, the European Union funded a project to calculate likelihood ratios using a software package with a user friendly interface called SAILR. Calculating the likelihood ratio is mostly done by using feature based models. A feature based model used by SAILR will be elaborated according to a glass comparison example. When the feature based model is illustrated, an extension on the model will be given using a non-parametric function. The discussed models will be elaborated and applied on test data from and international drugs comparison project using SAILR. As an alternative to feature based models, a score based model is introduced and compared to the previous drugs comparison results of the feature based model.