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Article: The small-sample efficiency of some recently proposed multivariate measures of location

TitleThe small-sample efficiency of some recently proposed multivariate measures of location
Authors
KeywordsMedian ball algorithm
Minimum generalized variance technique
OGK estimator
Projection methods
Robust methods
Skipped estimators of location
TBS estimator
Issue Date2010
PublisherWayne State University, College of Education. The Journal's web site is located at http://www.jmasm.com/
Citation
Journal Of Modern Applied Statistical Methods, 2010, v. 9 n. 1, p. 28-42 How to Cite?
AbstractNumerous multivariate robust measures of location have been proposed and many have been found to be unsatisfactory in terms of their small-sample efficiency. Several new measures of location have recently been derived, however, nothing is known about their small-sample efficiency or how they compare to the sample mean under normality. This research compared the efficiency for p = 2, 5, and 8 with sample sizes n = 20 and 50 for p-variate data. Although previous studies indicate that so-called skipped estimators are efficient, this study found that variations of this approach can perform poorly when n is small and p exceeds 5. One of the best estimators was found to be a skipped estimator where outliers detected by a projection method are eliminated. The TBS, OGK and RMBA estimators were included and; in some cases, they performed well, however, serious exceptions were identified suggesting that a skipped estimator based on a projection-type outlier detection method is preferable based on efficiency. © 2010 JMASM, Inc.
Persistent Identifierhttp://hdl.handle.net/10722/139772
ISSN
2015 SCImago Journal Rankings: 0.144
References

 

DC FieldValueLanguage
dc.contributor.authorNg, Men_HK
dc.contributor.authorWilcox, RRen_HK
dc.date.accessioned2011-09-23T05:55:45Z-
dc.date.available2011-09-23T05:55:45Z-
dc.date.issued2010en_HK
dc.identifier.citationJournal Of Modern Applied Statistical Methods, 2010, v. 9 n. 1, p. 28-42en_HK
dc.identifier.issn1538-9472en_HK
dc.identifier.urihttp://hdl.handle.net/10722/139772-
dc.description.abstractNumerous multivariate robust measures of location have been proposed and many have been found to be unsatisfactory in terms of their small-sample efficiency. Several new measures of location have recently been derived, however, nothing is known about their small-sample efficiency or how they compare to the sample mean under normality. This research compared the efficiency for p = 2, 5, and 8 with sample sizes n = 20 and 50 for p-variate data. Although previous studies indicate that so-called skipped estimators are efficient, this study found that variations of this approach can perform poorly when n is small and p exceeds 5. One of the best estimators was found to be a skipped estimator where outliers detected by a projection method are eliminated. The TBS, OGK and RMBA estimators were included and; in some cases, they performed well, however, serious exceptions were identified suggesting that a skipped estimator based on a projection-type outlier detection method is preferable based on efficiency. © 2010 JMASM, Inc.en_HK
dc.languageengen_US
dc.publisherWayne State University, College of Education. The Journal's web site is located at http://www.jmasm.com/en_HK
dc.relation.ispartofJournal of Modern Applied Statistical Methodsen_HK
dc.subjectMedian ball algorithmen_HK
dc.subjectMinimum generalized variance techniqueen_HK
dc.subjectOGK estimatoren_HK
dc.subjectProjection methodsen_HK
dc.subjectRobust methodsen_HK
dc.subjectSkipped estimators of locationen_HK
dc.subjectTBS estimatoren_HK
dc.titleThe small-sample efficiency of some recently proposed multivariate measures of locationen_HK
dc.typeArticleen_HK
dc.identifier.emailNg, M: marieng@hku.hken_HK
dc.identifier.authorityNg, M=rp01451en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-82055184007en_HK
dc.identifier.hkuros192644en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-82055184007&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume9en_HK
dc.identifier.issue1en_HK
dc.identifier.spage28en_HK
dc.identifier.epage42en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridNg, M=36155754200en_HK
dc.identifier.scopusauthoridWilcox, RR=7202527113en_HK

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