The University of Southampton
×
Filter your search:
University of Southampton Institutional Repository

Fast algorithms for the minimum volume estimator

Fast algorithms for the minimum volume estimator
Fast algorithms for the minimum volume estimator
The minimum volume ellipsoid (MVE) estimator is an important tool in robust regression and outlier detection in statistics. We develop fast and efficient algorithms for the MVE estimator problem and discuss how they can be implemented efficiently. The novelty of our approach stems from the recent developments in the first-order algorithms for solving the related minimum volume enclosing ellipsoid problem. Comparative computational results are provided which demonstrate the strength of the algorithms.
Minimum volume estimator, Outlier detection, Robust regression
0925-5001
351-370
Ahipasaoglu, Selin Damla
d69f1b80-5c05-4d50-82df-c13b87b02687
Ahipasaoglu, Selin Damla
d69f1b80-5c05-4d50-82df-c13b87b02687

Ahipasaoglu, Selin Damla (2015) Fast algorithms for the minimum volume estimator. Journal of Global Optimization, 62 (2), 351-370. (doi:10.1007/s10898-014-0233-8).

Record type: Article

Abstract

The minimum volume ellipsoid (MVE) estimator is an important tool in robust regression and outlier detection in statistics. We develop fast and efficient algorithms for the MVE estimator problem and discuss how they can be implemented efficiently. The novelty of our approach stems from the recent developments in the first-order algorithms for solving the related minimum volume enclosing ellipsoid problem. Comparative computational results are provided which demonstrate the strength of the algorithms.

This record has no associated files available for download.

More information

e-pub ahead of print date: 26 August 2014
Published date: 18 June 2015
Keywords: Minimum volume estimator, Outlier detection, Robust regression

Identifiers

Local EPrints ID: 443174
URI: http://eprints.soton.ac.uk/id/eprint/443174
DOI: doi:10.1007/s10898-014-0233-8
ISSN: 0925-5001
PURE UUID: 57d356d5-af7e-4683-9742-24232dce091e
ORCID for Selin Damla Ahipasaoglu: ORCID iD orcid.org/0000-0003-1371-315X

Catalogue record

Date deposited: 13 Aug 2020 16:38
Last modified: 17 Mar 2024 04:03

Export record

Altmetrics

Contributors

Author: Selin Damla Ahipasaoglu ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Library staff additional information
Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×