The second part of a two-part work on multivariate analysis is concerned with the more specialized techniques that follow on from the basic theory presented in part one. Topics covered include discriminant analysis, cluster analysis, path analysis, graphical modelling, latent variable techniques, repeated measures analysis and growth curve models. Modern problems and techniques, such as handling of high dimensional data and the use of neural networks are featured and the book concludes with a discussion of strategic aspects of multivariate analysis.
Discriminant analysis; cluster analysis; latent structure models; path analysis and graphical models; growth curve analysis; shape analysis; spectrometric data; directional data; distances between distributions.
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