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Article: On extended partially linear single-index models

TitleOn extended partially linear single-index models
Authors
KeywordsAlpha-mixing
Kernel smoothing
Nonlinear time series
Partially linear model
Single-index model
Issue Date1999
PublisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/
Citation
Biometrika, 1999, v. 86 n. 4, p. 831-842 How to Cite?
AbstractAiming to explore the relation between the response y and the stochastic explanatory vector variable X beyond the linear approximation, we consider the single-index model, which is a well-known approach in multidimensional cases. Specifically, we extend the partially linear single-index model to take the form y = β0 TX + φ(θ0 TX) + ε, where ε is a random variable with Eε = 0 and var(ε) = σ2, unknown, β0 and θ0 are unknown parametric vectors and φ(.) is an unknown real function. The model is also applicable to nonlinear time series analysis. In this paper, we propose a procedure to estimate the model and prove some related asymptotic results. Both simulated and real data are used to illustrate the results. © 1999 Biometrika Trust.
Persistent Identifierhttp://hdl.handle.net/10722/82742
ISSN
2015 Impact Factor: 1.13
2015 SCImago Journal Rankings: 2.801
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorXia, Yen_HK
dc.contributor.authorTong, Hen_HK
dc.contributor.authorLi, WKen_HK
dc.date.accessioned2010-09-06T08:32:53Z-
dc.date.available2010-09-06T08:32:53Z-
dc.date.issued1999en_HK
dc.identifier.citationBiometrika, 1999, v. 86 n. 4, p. 831-842en_HK
dc.identifier.issn0006-3444en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82742-
dc.description.abstractAiming to explore the relation between the response y and the stochastic explanatory vector variable X beyond the linear approximation, we consider the single-index model, which is a well-known approach in multidimensional cases. Specifically, we extend the partially linear single-index model to take the form y = β0 TX + φ(θ0 TX) + ε, where ε is a random variable with Eε = 0 and var(ε) = σ2, unknown, β0 and θ0 are unknown parametric vectors and φ(.) is an unknown real function. The model is also applicable to nonlinear time series analysis. In this paper, we propose a procedure to estimate the model and prove some related asymptotic results. Both simulated and real data are used to illustrate the results. © 1999 Biometrika Trust.en_HK
dc.languageengen_HK
dc.publisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/en_HK
dc.relation.ispartofBiometrikaen_HK
dc.rightsBiometrika. Copyright © Oxford University Press.en_HK
dc.subjectAlpha-mixingen_HK
dc.subjectKernel smoothingen_HK
dc.subjectNonlinear time seriesen_HK
dc.subjectPartially linear modelen_HK
dc.subjectSingle-index modelen_HK
dc.titleOn extended partially linear single-index modelsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0006-3444&volume=86&issue=4&spage=831&epage=842&date=1999&atitle=On+extended+partially+linear+single-index+modelsen_HK
dc.identifier.emailLi, WK: hrntlwk@hku.hken_HK
dc.identifier.authorityLi, WK=rp00741en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1093/biomet/86.4.831-
dc.identifier.scopuseid_2-s2.0-0011336701en_HK
dc.identifier.hkuros47759en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0011336701&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume86en_HK
dc.identifier.issue4en_HK
dc.identifier.spage831en_HK
dc.identifier.epage842en_HK
dc.identifier.isiWOS:000084833000007-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridXia, Y=7403027730en_HK
dc.identifier.scopusauthoridTong, H=7201359749en_HK
dc.identifier.scopusauthoridLi, WK=14015971200en_HK

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