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Bayesian classification of Neolithic tools

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Abstract:

The classification of Neolithic tools by using cluster analysis enables archaeologists to understand the function of the tools and the technological and cultural conditions of the societies that made them. In this paper, Bayesian classification is adopted to analyse data which raise the question whether the observed variability, e.g. the shape and dimensions of the tools, is related to their use. The data present technical difficulties for the practitioner, such as the presence of mixed mode data, missing data and errors in variables. These complications are overcome by employing a finite mixture model and Markov chain Monte Carlo methods. The analysis uses prior information which expresses the archaeologist's belief that there are two tool groups that are similar to contemporary adzes and axes. The resulting mixing densities provide evidence that the morphological dimensional variability among tools is related to the existence of these two tool groups.

Keywords: Bayesian analysis; Cluster analysis; Errors in variables; Markov chain Monte Carlo method; Missing data; Mixed mode data

Document Type: Research Article

Affiliations: Athens University of Economics and Business, Greece

Publication date: February 1, 1998

bpl/rssc/1998/00000047/00000002/art00112
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