Abstract
Foreword 1. Clustering from the perspective of combinatorial data analysis 2. Developments in principal component analysis 3. Canonical discriminant analysis: comparison of resampling methods and convex-hull approximation 4. Nonlinear methods for the analysis of homogeneity and heterogeneity 5. Principles component models for patterned covariance matrices, with applications to canonical correlation analysis of several sets of variables 6. Orthogonal and projection Procrustes analysis 7. Graphical Modelling 8. Convergent computation by iterative majorization: theory and applications in multidimensional data analysis 9. Biplot display of multivariate categorical data, with comments on multiple correspondence analysis 10. MANOVA biplots for two-way contingency tables 11. Some tools for the multivariate analysis of functional data 12. A general theory of biplots References
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