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Principal components analysis of mixed data

  • J. O. Ramsay
  • B. W. Silverman
Part of the Springer Series in Statistics book series (SSS)

Abstract

It is a characteristic of statistical methodology that problems do not always fall into neat categories. In the context of the methods discussed in this book, we often have both a vector of data and an observed function on each individual of interest. In this chapter, we consider some ways of approaching such mixed data, extending the ideas of PCA that we have already developed.

Keywords

Principal Component Analysis Principal Component Score Functional Part Hybrid Data Vector Part 
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 1997

Authors and Affiliations

  • J. O. Ramsay
    • 1
  • B. W. Silverman
    • 2
  1. 1.Department of PsychologyMcGill UniversityMontrealCanada
  2. 2.Department of MathematicsUniversity of BristolBristolUK

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