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Article: Testing the adequacy for a general linear errors-in-variables model

TitleTesting the adequacy for a general linear errors-in-variables model
Authors
KeywordsBias correction
errors-in-variables model
lack-of-fit test
Issue Date2005
PublisherAcademia Sinica, Institute of Statistical Science. The Journal's web site is located at http://www.stat.sinica.edu.tw/statistica/
Citation
Statistica Sinica, 2005, v. 15 n. 4, p. 1049-1068 How to Cite?
AbstractIn testing the adequacy of a regression model, the conditional expectation of the residuals given the observed covariate is often employed to construct lack-of-fit tests. However, in the errors-in-variables model, the resiudal is biased and cannot be used directly. In this paper, by correcting for the bias, we suggest lack-of-fit tests of score type for a general linear errors-in-variables model. The polynomial model is a special case. The tests are asymptotically chi-squared under the null hypothesis. The choice of scores involved in the test statistics and the power properties are investigated. A simulation study shows that the tests perform well. Application to two data sets is also made. The approach can readily be extended to handle general parametric models.
Persistent Identifierhttp://hdl.handle.net/10722/45344
ISSN
2015 Impact Factor: 0.838
2015 SCImago Journal Rankings: 2.292

 

DC FieldValueLanguage
dc.contributor.authorZhu, LXen_HK
dc.contributor.authorCui, HJen_HK
dc.date.accessioned2007-10-30T06:23:23Z-
dc.date.available2007-10-30T06:23:23Z-
dc.date.issued2005en_HK
dc.identifier.citationStatistica Sinica, 2005, v. 15 n. 4, p. 1049-1068en_HK
dc.identifier.issn1017-0405en_HK
dc.identifier.urihttp://hdl.handle.net/10722/45344-
dc.description.abstractIn testing the adequacy of a regression model, the conditional expectation of the residuals given the observed covariate is often employed to construct lack-of-fit tests. However, in the errors-in-variables model, the resiudal is biased and cannot be used directly. In this paper, by correcting for the bias, we suggest lack-of-fit tests of score type for a general linear errors-in-variables model. The polynomial model is a special case. The tests are asymptotically chi-squared under the null hypothesis. The choice of scores involved in the test statistics and the power properties are investigated. A simulation study shows that the tests perform well. Application to two data sets is also made. The approach can readily be extended to handle general parametric models.en_HK
dc.format.extent216082 bytes-
dc.format.extent1786 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherAcademia Sinica, Institute of Statistical Science. The Journal's web site is located at http://www.stat.sinica.edu.tw/statistica/en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectBias correctionen_HK
dc.subjecterrors-in-variables modelen_HK
dc.subjectlack-of-fit testen_HK
dc.titleTesting the adequacy for a general linear errors-in-variables modelen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1017-0405&volume=15&issue=4&spage=1049&epage=1068&date=2005&atitle=Testing+the+adequacy+for+a+general+linear+errors-in-variables+modelen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.scopuseid_2-s2.0-30744457301-

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