A STUDY OF CHINESE PORCELAIN RAW MATERIALS FOR DING,XING, GONGXIAN AND DEHUA WARES*

The raw material used largely determines the type and quality of porcelain produced. Twenty-three raw materials used for making Ding, Xing, Gongxian and Dehua porcelain bodies were studied using principal component analysis. Results show that for Dehua wares, only one raw material was used. For Ding wares, although there were many possible raw materials, the use of one alone is unlikely. Lingshan clay was the main raw material but it has to be mixed with other raw materials: Pinjiawa clay, quartz, feldspar and dolomite. The Xing pieces can be divided into three groups and Gongxian wares into two groups, which are discussed in detail.     

MULTIVARIATE ANALYSIS OF THE ENERGY DISPERSIVE X-RAY FLUORESCENCE RESULTS FROM BLUE AND WHITE CHINESE PORCELAINS*

The energy dispersive X-ray fluorescence technique was employed to study non-destructively the surface of 66 samples of Chinese porcelain, of different periods and origins, and determine the contents of 13 chemical elements, namely, Ti, Mn, Fe, Co, Ni, Cu, Zn, Ga, Pb, Rb, Sr, Y and Zr. Principal components analysis was performed on these 13 variables, and scatter plots, incorporating the first, second and third principal components, used to study the clustering behaviour of the data. Based on these results, discriminant analysis was then performed on the data, and discriminant functions established for attributing the period and origin of the porcelains.     

CYPRIOT BYZANTINE GLAZED POTTERY: A STUDY OF THE PAPHOS WORKSHOPS

Twenty‐five samples of Byzantine glazed pottery from two archaeological sites between Limassol and Paphos region (Cyprus), dated between the 12th and 15th century ad were studied using micro X‐ray fluorescence spectroscopy, scanning electron microscopy and X‐ray diffraction analysis. It was found that all the glazes contain lead, following the main manufacturing process of medieval pottery in the Mediterranean territory, while some of them contain tin, possibly for better opacity. Furthermore, it is shown that copper, iron and cobalt with nickel are responsible for the decoration colours. Finally, the application of principal component analysis revealed significant differentiation for some of the samples.     

MULTIVARIATE ANALYSIS OF COMPOSITIONAL DATA: APPLIED COMPARISONS FAVOUR STANDARD PRINCIPAL COMPONENTS ANALYSIS OVER AITCHISON'S LOGLINEAR CONTRAST METHOD

There has been debate about whether standard principal components analysis is appropriate for the multivariate analysis of compositional data (e.g. oxide composition of glass), Loglinear transformation has been recommended by Aitchison as a prerequisite. This paper argues that previous comparisons of methodological merits have tended to circularity of argument by making assumptions about the form of a good multivariate result. To break the circularity of argument the authors have introduced randomized variables into five data sets. A good result must recognize these randomized variables as noise and place them near the centroid of the principal components scattergram of variable loadings. Standard principal components analysis is found to perform better than loglinear transformation in its ability to recognize the randomized variables. It is concluded that loglinear transformation tends to introduce spurious structure into a table of compositional data. This paper is followed by a comment by M. J. Baxter.     

MODIFIED MAHALANOBIS FILTERS FOR GROUPING POTTERY BY CHEMICAL COMPOSITION*

A statistical procedure for grouping pottery in provenance studies by chemical data is presented, which now is routinely in use in our laboratory. It is based on the Mahalanobis filter method and X² -statistics, and can be used for both establishing groups and assigning single sherds to already known groups, thus replacing principal components analysis or cluster analysis and avoiding their problems in grouping pottery. The new method is able to consider correlations, uncertainties of measurement and constant shifts of the data in case of dilution. In particular, considering dilution effects results in both a better assignment to and separation of reference groups and is also equivalent to the compositional data approach, if log-transformed data are used. Other distortions of data (e.g., mixing of clays) can also be considered.     

DETECTING MULTIVARIATE OUTLIERS IN ARTEFACT COMPOSITIONAL DATA*

Multivariate statistical analysis of artefact compositional data, usually undertaken to investigate structure in the data, often incidentally reveals the presence of multivariate outliers. Much statistical methodology dealing with the detection of such outliers is not well suited to archaeometric data that, in the event, consist of two or more groups. The paper provides examples to illustrate the importance of detecting and dealing with outliers, and critically examines a range of different approaches to outlier detection. The examples show that cluster analysis, the technique most widely used for this purpose, can fail to reveal outliers clearly identified by other methods.     

A PROVENANCE STUDY OF POTTERY FROM ARCHAEOLOGICAL SITES NEAR CANOSA,PUGLIA (ITALY)*

Studies have been carried out to assess the provenance of selected pottery excavated at archaeological sites near Canosa, Puglia (Italy). Sixty-six sherds, ranging in date from the mid-seventh century BC to the beginning of the third century BC, were analysed by atomic absorption spectroscopy and 16 elements were determined. The analysis data were subjected to multivariate classification procedures. Tests showed that the majority of the examined sherds came from ancient local kilns; a probable Ionian origin was established for some other sherds, while the rest were of unknown origin.     

RQ-MODE PRINCIPAL COMPONENTS ANALYSIS OF CERAMIC COMPOSITIONAL DATA*

RQ-mode principal components analysis (PCA) is a means for calculating variable and object loadings on the same axes, so that elements can be displayed along with data points on a single diagram. The biplots resulting from RQ-mode PCA preserve both Euclidean relations among the objects and variance-covariance structure. When used with data on the chemical composition of archaeological pottery, such biplots facilitate recognizing compositional subgroups and determining the chemical basis of group separation. RQ-mode PCA is illustrated in this paper with neutron activation data on Mesoamerican Plumbate pottery.     

DETERMINING POTTERY PROVENANCE: APPLICATION OF A NEW HIGH-PRECISION X-RAY FLUORESCENCE METHOD AND COMPARISON WITH INSTRUMENTAL NEUTRON ACTIVATION ANALYSIS*

A recently developed high-precision X-ray fluorescence (XRF) method, applied for the first time to the study of archaeological pottery, determines the abundances of 13 trace and four major elements from one X-ray spectrum acquired over a 1000 second counting interval. For replicate archaeological samples, the short-term and long-term measurement precisions were close to 1% for the ten elements measured with highest precision. These are comparable to the best results achieved on replicates of clay and pottery standards, and obsidian, using instrumental neutron activation analysis (INAA). High-precision XRF analysis, however, does not require a nuclear facility, and is markedly preferable to INAA in terms of the ease of both sample preparation and analytical procedure. Consequently, element abundance data can usually be provided by a single analyst within a few hours after the start of sample preparation. The accuracy of the method, determined by comparison with data of other workers on eight standard reference materials, averaged 2.4% for the ten best-agreeing elements. The effectiveness of the method for determining pottery provenance is demonstrated for a difficult problem, in which high-precision XRF analysis successfully distinguished the products of two nearby pottery manufacturers in Roman Galilee (Shikhin and Nahif) that had not been clearly differentiated by INAA. The greater effectiveness of high-precision XRF than INAA in this provenance study is a result of the different array of elements measured, and the higher precision obtained for certain elements, by XRF. These results suggest that high precision XRF has potential broad applicability for pottery provenance studies.     

MATCHING PAST AND PRESENT CERAMIC PRODUCTION IN THE BANDA AREA (GHANA): IMPROVING THE ANALYTICAL PERFORMANCE OF NEUTRON ACTIVATION ANALYSIS IN ARCHAEOLOGY USING MULTIVARIATE ANALYSIS TECHNIQUES*

The transfer of advances in chemometrics into archaeometric research opens up a wide range of new application possibilities in this rapidly developing field. Neutron activation analysis (NAA) of ceramic samples from the Banda Traditional Area (west‐central Ghana) combined with chemometrics allowed us to establish a link between current and ancient systems of ceramics production in the historic settlements of Kuulo Kataa and Makala Kataa. Principal component analysis (PCA) and the soft independent modelling of class analogy (SIMCA) method were applied to the Das Dores Cruz data set in order to unequivocally determine the geographical origin of the diverse archaeological samples. After global autoscaling pretreatment, PCA analysis showed a clear difference between samples from different locations. The classification models obtained by SIMCA showed a classification ability of 100% and a prediction ability of 97.7%, with a mean sensitivity of 84% and a specificity of 100% for the three categories. The application of SIMCA showed that some NAA variables (elements) were more important than others in terms of geographical classification. With the class models that we obtained, we were able to determine the origin of the ancient remains. SIMCA has proved to be a powerful technique for the class modelling of archaeological data.