Robust Statistics

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

Abstract

Outliers are sample values which cause surprise in relation to the majority of the sample. This is not a pejorative term; outliers may be correct, but they should always be checked for transcription errors. They can play havoc with standard statistical methods, and many robust and resistant methods have been developed since 1960 to be less sensitive to outliers.

Keywords

Robust Regression Robust Statistics Breakdown Point Resistant Method Little Trim Square 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    These routines are available from statlib (see Appendix C) and include code for the resistant methods discussed in Section 8.4.Google Scholar
  2. 2.
    A term attributed by Dixon (1960) to Charles R Winsor.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

Personalised recommendations