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Modern Applied Statistics With S

The relative influence of individual, social and physical environment determinants of physical activity.

Exploring and identifying structure is even more important for multivariate data than univariate data, given the difficulties in graphically presenting multivariate data and the comparative lack of parametric models to represent it. Unfortunately, such exploration is also inherently more difficult.

Multivariate Density Estimation

The statistical analysis of compositional data

Detection of lung cancer with volatile markers in the breath

This text explains to new readers the various methods of multivariate analysis used in archaeological practice. It focuses on the techniques available, including: principal component analysis; correspondence analysis; cluster analysis; and discriminant analysis. Critically reviewing their use in practice, the book describes other areas in which they could be usefully applied. Methods where software packages are available are emphasized.

Exploratory Multivariate Analysis in Archaeology

Data sets and problems kernel density estimates sampling regression and related models multivariate methods principal component analysis and related methods cluster analysis discrimination and classification missing data and outliers analysis if tubular data computer-intensive methods spatial analysis bayesian methods absolute dating - radiocarbon calibration relative dating - seriation quantification lead isotope analysis the megalithic yard comparing assembage diversity shoerter studies.

Statistics in Archaeology

Some Archaeological Applications of Kernel Density Estimates

Standardization and Transformation in Principal Component Analysis, with Applications to Archaeometry

Compositional data arise commonly in archaeometry, in the study of artefact compositions where the variables measured either sum to 100%, or can be viewed as a subset of such a set of variables. There has been debate in Archaeometry about the appropriate way to analyse such data statistically, which amounts to argument about how the data should be transformed prior to statistical analysis. This paper reviews aspects of the debate and illustrates, using both simulated and real data, that what has been proposed as the 'correct' theoretical approach-log-ratio analysis-does not always work well. The reasons for this are discussed.

Mike Baxter

Papers

Exploratory Multivariate Analysis in Archaeology

Statistics in Archaeology

Some Archaeological Applications of Kernel Density Estimates

Standardization and Transformation in Principal Component Analysis, with Applications to Archaeometry

Log-ratio compositional data analysis in archaeometry*