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Article: Generalized estimating equations for variance and covariance parameters in regression credibility models

TitleGeneralized estimating equations for variance and covariance parameters in regression credibility models
Authors
KeywordsCredibility theory
Generalized estimating equations
IM31
Moving average errors
Regression credibility models
Issue Date2006
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/ime
Citation
Insurance: Mathematics And Economics, 2006, v. 39 n. 1, p. 99-113 How to Cite?
AbstractWe propose a regression credibility model that extends the one introduced by Hachemeister [Hachemeister, C.A., 1975. Credibility for regression models with application to trend. In: Kahn, P.M. (Ed.), Credibility: Theory and Applications. Academic Press, New York, pp. 129-163] by encapsulating a moving average error structure. Generalized estimating equations (GEE) are developed to estimate the unknown variance and covariance parameters. A comprehensive account is presented to demonstrate the implementation of the Bühlmann and Bühlmann-Straub frameworks under the model proposed and how GEE estimators are worked out within these two frameworks. A simulation study is conducted to compare the performance of the proposed GEE estimators with the alternative Bühlmann, Bühlmann-Straub, and Cossette and Luong's [Cossette, H., Luong, A., 2003. Generalised least squares estimators for creditibilty regression models with moving average errors. Insurance Math. Econom. 32, 281-293] GLS estimators. The GEE estimators are found to perform well, especially when the error terms are correlated. © 2006 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/83000
ISSN
2015 Impact Factor: 1.378
2015 SCImago Journal Rankings: 1.000
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLo, CHen_HK
dc.contributor.authorFung, WKen_HK
dc.contributor.authorZhu, ZYen_HK
dc.date.accessioned2010-09-06T08:35:48Z-
dc.date.available2010-09-06T08:35:48Z-
dc.date.issued2006en_HK
dc.identifier.citationInsurance: Mathematics And Economics, 2006, v. 39 n. 1, p. 99-113en_HK
dc.identifier.issn0167-6687en_HK
dc.identifier.urihttp://hdl.handle.net/10722/83000-
dc.description.abstractWe propose a regression credibility model that extends the one introduced by Hachemeister [Hachemeister, C.A., 1975. Credibility for regression models with application to trend. In: Kahn, P.M. (Ed.), Credibility: Theory and Applications. Academic Press, New York, pp. 129-163] by encapsulating a moving average error structure. Generalized estimating equations (GEE) are developed to estimate the unknown variance and covariance parameters. A comprehensive account is presented to demonstrate the implementation of the Bühlmann and Bühlmann-Straub frameworks under the model proposed and how GEE estimators are worked out within these two frameworks. A simulation study is conducted to compare the performance of the proposed GEE estimators with the alternative Bühlmann, Bühlmann-Straub, and Cossette and Luong's [Cossette, H., Luong, A., 2003. Generalised least squares estimators for creditibilty regression models with moving average errors. Insurance Math. Econom. 32, 281-293] GLS estimators. The GEE estimators are found to perform well, especially when the error terms are correlated. © 2006 Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/imeen_HK
dc.relation.ispartofInsurance: Mathematics and Economicsen_HK
dc.rightsInsurance Mathematics and Economics. Copyright © Elsevier BV.en_HK
dc.subjectCredibility theoryen_HK
dc.subjectGeneralized estimating equationsen_HK
dc.subjectIM31en_HK
dc.subjectMoving average errorsen_HK
dc.subjectRegression credibility modelsen_HK
dc.titleGeneralized estimating equations for variance and covariance parameters in regression credibility modelsen_HK
dc.typeArticleen_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.insmatheco.2006.01.006en_HK
dc.identifier.scopuseid_2-s2.0-33745647669en_HK
dc.identifier.hkuros133708en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33745647669&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume39en_HK
dc.identifier.issue1en_HK
dc.identifier.spage99en_HK
dc.identifier.epage113en_HK
dc.identifier.isiWOS:000239256100007-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridLo, CH=23095088400en_HK
dc.identifier.scopusauthoridFung, WK=13310399400en_HK
dc.identifier.scopusauthoridZhu, ZY=23487505000en_HK

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