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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10016/15655
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| Title: | A subsampling method for the computation of multivariate estimators with high breakdown point |
| Author(s): | Juan, Jesús
Prieto, Francisco J. |
| Publisher: | American Statistical Association
Institute of Mathematical Statistics
Interface Foundation of America
Taylor & Francis |
| Issued date: | 1995 |
| Citation: | Journal of Computational and Graphical Statistics, 1995, v. 4, n. 4, p. 1-16 |
| URI: | http://hdl.handle.net/10016/15655 |
| ISSN: | 1061-8600 |
| Abstract: | All known robust location and scale estimators with high breakdown point for multivariate samples are very expensive to compute. In practice, this computation has to be carried out using an approximate subsampling procedure. In this article we describe an altemative subsampling scheme, applicable to both the Stahel-Donoho estimator and the minimum volume ellipsoid estimator, with the property that the number of subsamples required can be substantially reduced with respect to the standard subsampling procedures used in both cases. We also discuss some bias and variability properties of the estimator obtained from the proposed subsampling process |
| Sponsor: | The authors' work was partiaIly supported by CICYT grant ROB91-0244 and DGICYT grant PB93-0232 |
| Publisher version: | http://www.jstor.org/stable/1390859 |
| Keywords: | Minimum volume ellipsoid estimator
Outlier detection
Robust estimation
Stahel-Donoho estimator |
| Rights: | © American Statistical Association
© Institute of Mathematical Statistics
© Interface Foundation of America |
| Appears in Collections: | DES - Artículos de Revistas
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