Exact iterative computation of the robust multivariate minimum volume ellipsoid estimator

R. D. Cook, D. M. Hawkins, S. Weisberg

Research output: Contribution to journalArticlepeer-review

42 Scopus citations

Abstract

A widely used procedure for robust estimation of the scatter matrix of multivariate data is the 'minimum volume ellipsoid' or MVE estimator. This seeks to find the ellipsoid of minimum volume which covers at least half of the data. Not only is the MVE used in its own right, it is also the starting point for most other high breakdown estimators of multivariate location and scatter. To date however, no exact algorithm for computing the MVE has been defined. This deficiency makes the MVE method, and all other methods using the MVE as a starting point, irreproducible. This paper gives an exact algorithm for computing the MVE and uses this exact algorithm to evaluate the performance of the approximate algorithm currently used in most MVE implementations.

Original languageEnglish (US)
Pages (from-to)213-218
Number of pages6
JournalStatistics and Probability Letters
Volume16
Issue number3
DOIs
StatePublished - 1993

Bibliographical note

Funding Information:
This work is supported by National Science Foundation grants DMS-9001298 and DMS-9010983.

Keywords

  • Multivariate
  • high breakdown estimation
  • outliers

Fingerprint Dive into the research topics of 'Exact iterative computation of the robust multivariate minimum volume ellipsoid estimator'. Together they form a unique fingerprint.

Cite this