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Article: On the Underfitting and Overfitting Sets of Models Chosen by Order Selection Criteria

TitleOn the Underfitting and Overfitting Sets of Models Chosen by Order Selection Criteria
Authors
KeywordsAIC
BIC
Markov fields
Model selection
Regressions and autoregressions
Stable law
Strong consistency
Underfitting and overfitting
Weak consistency
Issue Date1999
PublisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/jmva
Citation
Journal Of Multivariate Analysis, 1999, v. 70 n. 2, p. 221-249 How to Cite?
AbstractFor a general class of order selection criteria, we establish analytic and non-asymptotic evaluations of both the underfitting and overfitting sets of selected models. These evaluations are further specified in various situations including regressions and autoregressions with finite or infinite variances. We also show how upper bounds for the misfitting probabilities and hence conditions ensuring the weak consistency can be derived from the given evaluations. Moreover, it is demonstrated how these evaluations, combined with a law of the iterated logarithm for some relevant statistic, can provide conditions ensuring the strong consistency of the model selection criterion used. © 1999 Academic Press.
Persistent Identifierhttp://hdl.handle.net/10722/132636
ISSN
2015 Impact Factor: 0.857
2015 SCImago Journal Rankings: 1.458
References

 

DC FieldValueLanguage
dc.contributor.authorGuyon, Xen_HK
dc.contributor.authorYao, JFen_HK
dc.date.accessioned2011-03-28T09:27:08Z-
dc.date.available2011-03-28T09:27:08Z-
dc.date.issued1999en_HK
dc.identifier.citationJournal Of Multivariate Analysis, 1999, v. 70 n. 2, p. 221-249en_HK
dc.identifier.issn0047-259Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/132636-
dc.description.abstractFor a general class of order selection criteria, we establish analytic and non-asymptotic evaluations of both the underfitting and overfitting sets of selected models. These evaluations are further specified in various situations including regressions and autoregressions with finite or infinite variances. We also show how upper bounds for the misfitting probabilities and hence conditions ensuring the weak consistency can be derived from the given evaluations. Moreover, it is demonstrated how these evaluations, combined with a law of the iterated logarithm for some relevant statistic, can provide conditions ensuring the strong consistency of the model selection criterion used. © 1999 Academic Press.en_HK
dc.languageengen_US
dc.publisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/jmvaen_HK
dc.relation.ispartofJournal of Multivariate Analysisen_HK
dc.subjectAICen_HK
dc.subjectBICen_HK
dc.subjectMarkov fieldsen_HK
dc.subjectModel selectionen_HK
dc.subjectRegressions and autoregressionsen_HK
dc.subjectStable lawen_HK
dc.subjectStrong consistencyen_HK
dc.subjectUnderfitting and overfittingen_HK
dc.subjectWeak consistencyen_HK
dc.titleOn the Underfitting and Overfitting Sets of Models Chosen by Order Selection Criteriaen_HK
dc.typeArticleen_HK
dc.identifier.emailYao, JF: jeffyao@hku.hken_HK
dc.identifier.authorityYao, JF=rp01473en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-0033174020en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0033174020&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume70en_HK
dc.identifier.issue2en_HK
dc.identifier.spage221en_HK
dc.identifier.epage249en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridGuyon, X=6602587667en_HK
dc.identifier.scopusauthoridYao, JF=7403503451en_HK

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