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Three estimators of the Mahalanobis distance in high-dimensional data
Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.ORCID iD: 0000-0002-3623-5034
2012 (English)In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, no 12, 2713-2720 p.Article in journal (Refereed) Published
Abstract [en]

This paper treats the problem of estimating the Mahalanobis distance for the purpose of detecting outliers in high-dimensional data. Three ridge-type estimators are proposed and risk functions for deciding an appropriate value of the ridge coefficient are developed. It is argued that one of the ridge estimator has particularly tractable properties, which is demonstrated through outlier analysis of real and simulated data.

Place, publisher, year, edition, pages
2012. Vol. 39, no 12, 2713-2720 p.
Keyword [en]
ridge estimators, increasing dimension data, Mahalanobis distance, adaptive estimator
National Category
Probability Theory and Statistics
Research subject
Economy
Identifiers
URN: urn:nbn:se:lnu:diva-22705DOI: 10.1080/02664763.2012.725464ISI: 000310130900013OAI: oai:DiVA.org:lnu-22705DiVA: diva2:574412
Available from: 2012-12-05 Created: 2012-12-05 Last updated: 2017-04-18Bibliographically approved

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Holgersson, ThomasKarlsson, Peter S.
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CiteExportLink to record
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Citation style
  • apa
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