Compositional data naturally arises from the scientific analysis of the chemical
composition of archaeological material such as ceramic and glass artefacts. Data of this
type can be explored using a variety of techniques, from standard multivariate methods
such as principal components analysis and cluster analysis, to methods based upon the
use of log-ratios. The general aim is to identify groups of chemically similar artefacts
that could potentially be used to answer questions of provenance.
This paper will demonstrate work in progress on the development of a documented
library of methods, implemented using the statistical package R, for the analysis of
compositional data. R is an open source package that makes available very powerful
statistical facilities at no cost. We aim to show how, with the aid of statistical software
such as R, traditional exploratory multivariate analysis can easily be used alongside, or
in combination with, specialist techniques of compositional data analysis.
The library has been developed from a core of basic R functionality, together with
purpose-written routines arising from our own research (for example that reported at
CoDaWork'03). In addition, we have included other appropriate publicly available
techniques and libraries that have been implemented in R by other authors. Available
functions range from standard multivariate techniques through to various approaches to
log-ratio analysis and zero replacement. We also discuss and demonstrate a small
selection of relatively new techniques that have hitherto been little-used in
archaeometric applications involving compositional data. The application of the library
to the analysis of data arising in archaeometry will be demonstrated; results from
different analyses will be compared; and the utility of the various methods discussedGeologische Vereinigung; Institut d’Estadística de Catalunya; International Association for Mathematical Geology; Patronat de l’Escola Politècnica Superior de la Universitat de Girona; Fundació privada: Girona, Universitat i Futur; Càtedra Lluís Santaló d’Aplicacions de la Matemàtica; Consell Social de la Universitat de Girona; Ministerio de Ciencia i Tecnología