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Article: Asymptotics of sliced inverse regression

TitleAsymptotics of sliced inverse regression
Authors
KeywordsAsymptotics
sliced inverse regression
dimension reduction
eigenvalues and eigenvectors
Issue Date1995
PublisherAcademia Sinica, Institute of Statistical Science. The Journal's web site is located at http://www.stat.sinica.edu.tw/statistica/
Citation
Statistica Sinica, 1995, v. 5 n. 2, p. 727-736 How to Cite?
AbstractSliced Inverse Regression is a method for reducing the dimension of the explanatory variables x in non-parametric regression problems. Li (1991) discussed a version of this method which begins with a partition of the range of y into slices so that the conditional covariance matrix of x given y can be estimated by the sample covariance matrix within each slice. After that the mean of the conditional covariance matrix is estimated by averaging the sample covariance matrices over all slices. Hsing and Carroll (1992) have derived the asymptotic properties of this procedure for the special case where each slice contains only two observations. In this paper we consider the case that each slice contains an arbitrary but fixed number of yi and more generally the case when the number of yi per slice goes to infinity. The asymptotic properties of the associated eigenvalues and eigenvectors are also obtained.
Persistent Identifierhttp://hdl.handle.net/10722/45363
ISSN
2015 Impact Factor: 0.838
2015 SCImago Journal Rankings: 2.292

 

DC FieldValueLanguage
dc.contributor.authorZhu, Len_HK
dc.contributor.authorNg, KWen_HK
dc.date.accessioned2007-10-30T06:23:47Z-
dc.date.available2007-10-30T06:23:47Z-
dc.date.issued1995en_HK
dc.identifier.citationStatistica Sinica, 1995, v. 5 n. 2, p. 727-736en_HK
dc.identifier.issn1017-0405en_HK
dc.identifier.urihttp://hdl.handle.net/10722/45363-
dc.description.abstractSliced Inverse Regression is a method for reducing the dimension of the explanatory variables x in non-parametric regression problems. Li (1991) discussed a version of this method which begins with a partition of the range of y into slices so that the conditional covariance matrix of x given y can be estimated by the sample covariance matrix within each slice. After that the mean of the conditional covariance matrix is estimated by averaging the sample covariance matrices over all slices. Hsing and Carroll (1992) have derived the asymptotic properties of this procedure for the special case where each slice contains only two observations. In this paper we consider the case that each slice contains an arbitrary but fixed number of yi and more generally the case when the number of yi per slice goes to infinity. The asymptotic properties of the associated eigenvalues and eigenvectors are also obtained.en_HK
dc.format.extent199086 bytes-
dc.format.extent2525 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.subjectAsymptoticsen_HK
dc.subjectsliced inverse regressionen_HK
dc.subjectdimension reductionen_HK
dc.subjecteigenvalues and eigenvectorsen_HK
dc.titleAsymptotics of sliced inverse regressionen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1017-0405&volume=5&issue=2&spage=727&epage=736&date=1995&atitle=Asymptotics+of+sliced+inverse+regressionen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.hkuros9239-

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