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Linear Statistical Models

  • W. N. Venables
  • B. D. Ripley
Part of the Statistics and Computing book series (SCO)

Abstract

Linear models form the core of classical statistics, and S provides extensive facilities to fit and investigate them. These work with a version of the Wilkinson-Rogers notation (Wilkinson & Rogers, 1973) for specifying models which we discuss in Section 6.2.

Keywords

Model Matrix Data Frame Heart Weight High Order Interaction Diagnostic Plot 
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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References

  1. 1.
    The Sex coefficient appears to be significant but this is misleading as this term is marginal to log(Bwt) %in% Sex and may be modified by a change of origin.Google Scholar
  2. 2.
    Marginal terms are sometimes removed in this way in order to calculate what are known as “Type III sums of squares” but we have yet to see a situation where this makes compelling statistical sense.Google Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • W. N. Venables
    • 1
  • B. D. Ripley
    • 2
  1. 1.Department of StatisticsUniversity of AdelaideAdelaideAustralia
  2. 2.University of OxfordOxfordEngland

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