Statistical Modelling of Artefact Compositional Data

Author: Baxter M.J.¹

Source: Archaeometry, Volume 43, Number 1, January 2001 , pp. 131-147(17)

Publisher: Blackwell Publishing

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Abstract:

Model-based methods for clustering artefacts, given their chemical composition, often assume sampling from a mixture of multivariate normal distributions and/or make explicit assumptions about the way in which a composition is formed. It is argued that, analysed within a modelling framework, several important and apparently competing methodologies are more similar than would initially appear. The opportunity is taken to note that models for populations are often not compatible with models for compositions, and that dilution correction—which can be accomplished in a variety of ways—can be interpreted as an attempt to resolve this problem.

Keywords: cluster analysis; data transformation; composition; dilution; mahalanobis distance; model; multivariate normality

Document Type: Research article

DOI: 10.1111/1475-4754.00008

Affiliations: 1: Department of Mathematics, Statistics and Operational Research, Nottingham Trent University, UK

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