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Brookhaven procedures for statistical analyses of multivariate archaeometric data

E. V. Sayre
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TLDR
This paper deals with methods found to be practical and useful in the evaluation of multi-component neutron activation analyses and related studies of archaeological artifacts at Brookhaven National Laboratory.
Abstract
The accumulation in various laboratories of large numbers of multi-component analyses of archaeological artifacts has required the development of increasingly more sophisticated methods for intercomparing these data and analyzing them statistically. A number of different methods of both clustering of specimens into groups and multivariate evaluation of group membership are possible. This paper deals with methods found to be practical and useful in the evaluation of multi-component neutron activation analyses and related studies of archaeological artifacts at Brookhaven National Laboratory. The methods were applied most extensively and successfully to data on pottery and related clays. The subject is treated under the following topics: the use of log normal distributions; clustering methods; preliminary univariate, element-by-element, evaluation of the groups indicated by clustering; multivariate probability calculations; the need for multivariate data handling; use of characteristic vectors of the variance-covariance matrix; standardized multivariant coordinates; the handling of missing data; and auxiliary programs. It is felt that multivariate techniques must ultimately be employed to resolve a set of data fully, but that much can be accomplished by more simple element-to-element methods. 6 figures. (RWR)

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Book ChapterDOI

A Systematic Approach to Obsidian Source Characterization

TL;DR: Multivariate statistical methods based on Mahalanobis D 2 enable robust rejection of erroneous source assignments and lead to sourcing of artifacts with a very high degree of confidence.
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Log-ratio compositional data analysis in archaeometry*

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