Robust regression with high coverage

An important parameter for several high breakdown regression algorithm estimators is the number of cases given weight one, called the coverage of the estimator. Increasing the coverage is believed to result in a more stable estimator, but the price paid for this stability is greatly decreased resistance to outliers. A simple modification of the algorithm can greatly increase the coverage and hence its statistical performance while maintaining high outlier resistance.

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Year of publication:	2003
Authors:	Olive, David J. ; Hawkins, Douglas M.
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 63.2003, 3, p. 259-266
Publisher:	Elsevier
Keywords:	Elemental sets LMS LTA LTS Outliers

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005074551