Principal Components Used with Other Multivariate Techniques

  • I. T. Jolliffe
Part of the Springer Series in Statistics book series (SSS)

Abstract

Principal component analysis is often used as a dimension-reducing technique within some other type of analysis. For example, Chapter 8 described the use of PCs as regressor variables in a multiple regression analysis. The present chapter discusses three multivariate techniques, namely discriminant analysis, cluster analysis and canonical correlation analysis; for each of these three techniques, examples are given in the literature which use PCA as a dimension-reducing technique.

Keywords

Cluster Analysis Discriminant Analysis Linear Discriminant Analysis Mahalanobis Distance Canonical Correlation Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1986

Authors and Affiliations

  • I. T. Jolliffe
    • 1
  1. 1.Mathematical InstituteUniversity of KentKentEngland

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