Mathematical and Statistical Properties of Sample Principal Components

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


The first part of this chapter will be similar in structure to Chapter 2, except that it will deal with properties of PCs obtained from a sample covariance (or correlation) matrix, rather than from a population covariance (or correlation) matrix. The first two sections of the chapter, as in Chapter 2, describe respectively many of the algebraic and geometric properties of PCs. Most of the properties discussed in Chapter 2 are almost the same for samples as for populations, and will only be mentioned again briefly. There are, however, some additional properties which are relevant only to sample PCs and these will be discussed more fully.


Singular Value Decomposition Maximum Likelihood Estimator Correlation Matrice Multivariate Normal Distribution Multivariate Normality 
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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