Like many document examiners I consider Huber and Headrick’s 1999 textbook, Handwriting Identification: Facts and Fundamentals, to be a seminal work.1
In my opinion, it is the best textbook written to date on the topic of handwriting identification. The authors provide a comprehensive overview as well as some less conventional perspectives on certain concepts and topics. In general I tend to agree with their position on many things. A bit of disclosure is need here: I was trained in the RCMP laboratory system; the same system in which Huber and Headrick were senior examiners and very influential. Hence, I tend to be somewhat biased towards their point-of-view.
But that does not mean I think their textbook is perfect. While it is well written and manages to present a plethora of topics in reasonable depth, some parts are incomplete or misleading; particularly when we take developments that have happened since it was written into account.
One area of particular interest to me relates to the evaluation of evidence; specifically evaluation done using a coherent logical (or likelihood-ratio) approach. I have posted elsewhere on the topic so I’m not going to re-hash the background or details any more than necessary.
This post will look at the topic of ‘Bayesian concepts’ as discussed by Huber and Headrick in their textbook. These concepts fall under the general topic of statistical inference found in Chapter 4 “The Premises for the Identification of Handwriting”. The sub-section of interest is #21 where the authors attempt to answer the question, “What Part Does Statistical Inference Play in the Identification Process?” Much of their answer in that sub-section relates to Bayesian philosophy, in general, and the application of the logical approach to evidence evaluation. However, while they introduce some things reasonably well, the discussion is ultimately very flawed and very much in need of correction. Or, at least, clarification.