Computing the Least Quartile Difference Estimator in the Plane
AbstractA common problem in linear regression is that largely aberrant values can strongly influence the results. The least quartile difference (LQD) regression estimator is highly robust, since it can resist up to almost 50% largely deviant data values without becoming extremely biased. Additionally, it shows good behavior on Gaussian data – in contrast to many other robust regression methods. However, the LQD is not widely used yet due to the high computational effort needed when using common algorithms, e.g. the subset algorithm of Rousseeuw and Leroy. For computing the LQD estimator for n data points in the plane, we propose a randomized algorithm with expected running time O(n2 log2 n) and an approximation algorithm with a running time of roughly O(n2 log n). It can be expected that the practical relevance of the LQD estimator will strongly increase thereby. --
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen in its series Technical Reports with number 2005,51.
Date of creation: 2005
Date of revision:
Contact details of provider:
Postal: Vogelpothsweg 78, D-44221 Dortmund
Phone: (0231) 755-3125
Fax: (0231) 755-5284
Web page: http://www.statistik.tu-dortmund.de/sfb475.html
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Struyf, Anja J. & Rousseeuw, Peter J., 1999. "Halfspace Depth and Regression Depth Characterize the Empirical Distribution," Journal of Multivariate Analysis, Elsevier, vol. 69(1), pages 135-153, April.
- Hossjer, O. & Croux, C. & Rousseeuw, P. J., 1994.
"Asymptotics of Generalized S-Estimators,"
Journal of Multivariate Analysis,
Elsevier, vol. 51(1), pages 148-177, October.
- Hössjer, O. & Croux, Christophe & Rousseeuw, Peter, 1994. "Asymptotics of generalized S-estimators," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/205850, Katholieke Universiteit Leuven.
- Croux, Christophe & Rousseeuw, Peter & Hössjer, O., 1994. "Generalized S-estimators," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/205831, Katholieke Universiteit Leuven.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - German National Library of Economics).
If references are entirely missing, you can add them using this form.