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Conference Paper: Local polynomial modeling and bandwidth selection for time-varying linear models

TitleLocal polynomial modeling and bandwidth selection for time-varying linear models
Authors
KeywordsBandwidth selection
Least-squares
Local polynomial modeling
Time-varying linear model
Issue Date2009
PublisherIEEE.
Citation
The 7th International Conference on Information, Communications and Signal Processing (ICICS 2009), Macau, China, 8-10 December 2009. In Proceedings of the International Conference on Information, Communications and Signal Processing, 2009, p. 1-5 How to Cite?
AbstractThis paper proposes a local polynomial modeling approach and bandwidth selection algorithm for estimating time-varying linear models (TVLM). The time-varying coefficients of a TVLM are modeled locally by polynomials and estimated using least-squares estimation with a kernel having a certain bandwidth or support. Asymptotic behavior of the proposed estimator is established and it shows that there exists an optimal local bandwidth which minimizes the weighted mean squared error (MSE). A data-driven variable bandwidth selection method is also proposed to estimate this optimal bandwidth. Simulation results show that the proposed LPM method with adaptive bandwidth selection outperforms conventional TVLM identification methods in a large variety of testing conditions. ©2009 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/126154
ISBN
References

 

DC FieldValueLanguage
dc.contributor.authorChan, SCen_HK
dc.contributor.authorZhang, ZGen_HK
dc.date.accessioned2010-10-31T12:12:43Z-
dc.date.available2010-10-31T12:12:43Z-
dc.date.issued2009en_HK
dc.identifier.citationThe 7th International Conference on Information, Communications and Signal Processing (ICICS 2009), Macau, China, 8-10 December 2009. In Proceedings of the International Conference on Information, Communications and Signal Processing, 2009, p. 1-5en_HK
dc.identifier.isbn978-1-4244-4656-8-
dc.identifier.urihttp://hdl.handle.net/10722/126154-
dc.description.abstractThis paper proposes a local polynomial modeling approach and bandwidth selection algorithm for estimating time-varying linear models (TVLM). The time-varying coefficients of a TVLM are modeled locally by polynomials and estimated using least-squares estimation with a kernel having a certain bandwidth or support. Asymptotic behavior of the proposed estimator is established and it shows that there exists an optimal local bandwidth which minimizes the weighted mean squared error (MSE). A data-driven variable bandwidth selection method is also proposed to estimate this optimal bandwidth. Simulation results show that the proposed LPM method with adaptive bandwidth selection outperforms conventional TVLM identification methods in a large variety of testing conditions. ©2009 IEEE.en_HK
dc.languageengen_HK
dc.publisherIEEE.-
dc.relation.ispartofProceedings of the International Conference on Information, Communications and Signal Processingen_HK
dc.rightsInternational Conference on Information, Communications and Signal Processing. Copyright © IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.subjectBandwidth selectionen_HK
dc.subjectLeast-squaresen_HK
dc.subjectLocal polynomial modelingen_HK
dc.subjectTime-varying linear modelen_HK
dc.titleLocal polynomial modeling and bandwidth selection for time-varying linear modelsen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=978-1-4244-4656-8&volume=&spage=1&epage=5&date=2009&atitle=Local+polynomial+modeling+and+bandwidth+selection+for+time-varying+linear+models-
dc.identifier.emailChan, SC:scchan@eee.hku.hken_HK
dc.identifier.authorityChan, SC=rp00094en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICICS.2009.5397543en_HK
dc.identifier.scopuseid_2-s2.0-77949601444en_HK
dc.identifier.hkuros174345en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77949601444&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage1-
dc.identifier.epage5-
dc.description.otherThe 7th International Conference on Information, Communications and Signal Processing (ICICS 2009), Macau, China, 8-10 December 2009. In Proceedings of the International Conference on Information, Communications and Signal Processing, 2009, p. 1-5-
dc.identifier.scopusauthoridChan, SC=13310287100en_HK
dc.identifier.scopusauthoridZhang, ZG=8407277900en_HK

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