A new algorithm for resistant regression

Authors

  • A. Leroy Vrije Universiteit Brussel, Centrum voor Statistiek and O.R.
  • P. Rousseeuw Technische Hogeschool Delft, Onderafdeling Wiskunde & Informatica

Abstract

The ordinary least squares regression method is nota reliable tool in regression analysis without first diagnosing possible outliers present in the data set. The least median of squares regression technique (Rousseeuw 1984), which is designed to lessen the impact of outlying observations, is presented and some alternatives are given. The output of a Fortran implementation of this regression technique, called PROGRESS (Leroy and Rousseeuw 1984), is illustrated with an example. The results can be interpreted by means of graphical representation of the standardized residuals. It is showed how PROGRESS can be used as a diagnostic tool in regression analysis.

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Published

1986-06-01

How to Cite

Leroy, A., & Rousseeuw, P. (1986). A new algorithm for resistant regression. JORBEL - Belgian Journal of Operations Research, Statistics, and Computer Science, 26(2), 4–20. Retrieved from https://www.orbel.be/jorbel/index.php/jorbel/article/view/485

Issue

Vol. 26 No. 2 (1986)

Section

Articles