Trimming algorithms for clustering contaminated grouped data and their robustness

María Gallegos and Gunter Ritter ()

Advances in Data Analysis and Classification, 2009, vol. 3, issue 2, pages 135-167

Keywords: Statistical clustering; Robust clustering; Trimming algorithm; Breakdown points; Heteroscedasticity; HDBT ratio; Primary 62H30; Secondary 62F35 (search for similar items in EconPapers)
Date: 2009
View list of references

Downloads: (external link)
http://hdl.handle.net/10.1007/s11634-009-0044-9 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:spr:advdac:v:3:y:2009:i:2:p:135-167

Ordering information: This journal article can be ordered from
http://link.springer.de/orders.htm

Access Statistics for this article

Advances in Data Analysis and Classification is edited by H.-H. Bock, W. Gaul, A. Okada and M. Vichi

More articles in Advances in Data Analysis and Classification from Springer
Series data maintained by Christopher F Baum ().