The first edition of this book was the first comprehensive text written solely on principal component analysis. The second edition updates and substantially expands the original version, and is once again the definitive text on the subject. It includes core material, current research and a wide range of applications. Its length is nearly double that of the first edition.

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Introduction Properties of Population Principal Components Properties of Sample Principal Components Interpreting Principal Components: Examples Graphical Representation of Data Using Principal Components Choosing a Subset of Principal Components or Variables Principal Component Analysis and Factor Analysis Principal Components in Regression Analysis Principal Components Used with Other Multivariate Techniques Outlier Detection, Influential Observations and Robust Estimation Rotation and Interpretation of Principal Components Principal Component Analysis for Time Series and Other Non-Independent Data Principal Component Analysis for Special Types of Data * Generalizations and Adaptations of Principal Component Analysis