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Article: Identifying influential multinomial observations by perturbation

TitleIdentifying influential multinomial observations by perturbation
Authors
KeywordsConditional model
Diagnostics
Influence
Likelihood displacement
Maximum likelihood estimate
Perturbation
Issue Date2006
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/csda
Citation
Computational Statistics And Data Analysis, 2006, v. 50 n. 10, p. 2799-2821 How to Cite?
AbstractThe assessment of the influence of individual observations on the outcome of the analysis by perturbation has received a lot of attention for situations in which the observations are independent and identically distributed. However, no methods based on minor perturbations for carrying out such assessments are available in the context of multinomial models. A simultaneous perturbation scheme for the cell probabilities is proposed that leads to the definition of some new diagnostic tools for identifying influential observations. It is shown that the diagnostics derived extend and complement those based on the case deletion approach. The new diagnostics are used to explain departures from certain multinomial log-linear model assumptions. These tools are also used to give insights into genetic data for paternity. © 2005 Elsevier B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/82783
ISSN
2015 Impact Factor: 1.179
2015 SCImago Journal Rankings: 1.283
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorNyangoma, SOen_HK
dc.contributor.authorFung, WKen_HK
dc.contributor.authorJansen, RCen_HK
dc.date.accessioned2010-09-06T08:33:22Z-
dc.date.available2010-09-06T08:33:22Z-
dc.date.issued2006en_HK
dc.identifier.citationComputational Statistics And Data Analysis, 2006, v. 50 n. 10, p. 2799-2821en_HK
dc.identifier.issn0167-9473en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82783-
dc.description.abstractThe assessment of the influence of individual observations on the outcome of the analysis by perturbation has received a lot of attention for situations in which the observations are independent and identically distributed. However, no methods based on minor perturbations for carrying out such assessments are available in the context of multinomial models. A simultaneous perturbation scheme for the cell probabilities is proposed that leads to the definition of some new diagnostic tools for identifying influential observations. It is shown that the diagnostics derived extend and complement those based on the case deletion approach. The new diagnostics are used to explain departures from certain multinomial log-linear model assumptions. These tools are also used to give insights into genetic data for paternity. © 2005 Elsevier B.V. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/csdaen_HK
dc.relation.ispartofComputational Statistics and Data Analysisen_HK
dc.rightsComputational Statistics & Data Analysis. Copyright © Elsevier BV.en_HK
dc.subjectConditional modelen_HK
dc.subjectDiagnosticsen_HK
dc.subjectInfluenceen_HK
dc.subjectLikelihood displacementen_HK
dc.subjectMaximum likelihood estimateen_HK
dc.subjectPerturbationen_HK
dc.titleIdentifying influential multinomial observations by perturbationen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0167-9473&volume=50&spage=2799&epage=2821&date=2006&atitle=Identifying+influential+multinomial+observations+by+perturbationen_HK
dc.identifier.emailFung, WK: wingfung@hku.hken_HK
dc.identifier.authorityFung, WK=rp00696en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.csda.2005.04.023en_HK
dc.identifier.scopuseid_2-s2.0-33646105848en_HK
dc.identifier.hkuros133707en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33646105848&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume50en_HK
dc.identifier.issue10en_HK
dc.identifier.spage2799en_HK
dc.identifier.epage2821en_HK
dc.identifier.isiWOS:000237882800018-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridNyangoma, SO=6507989690en_HK
dc.identifier.scopusauthoridFung, WK=13310399400en_HK
dc.identifier.scopusauthoridJansen, RC=7201964208en_HK

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