Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0047-259X(03)00056-3
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dc.titleA chi-square test for dimensionality with non-Gaussian data
dc.contributor.authorBai, Z.D.
dc.contributor.authorHe, X.
dc.date.accessioned2014-10-28T05:08:59Z
dc.date.available2014-10-28T05:08:59Z
dc.date.issued2004-01
dc.identifier.citationBai, Z.D., He, X. (2004-01). A chi-square test for dimensionality with non-Gaussian data. Journal of Multivariate Analysis 88 (1) : 109-117. ScholarBank@NUS Repository. https://doi.org/10.1016/S0047-259X(03)00056-3
dc.identifier.issn0047259X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/104923
dc.description.abstractThe classical theory for testing the null hypothesis that a set of canonical correlation coefficients is zero leads to a chi-square test under the assumption of multi-normality. The test has been used in the context of dimension reduction. In this paper, we study the limiting distribution of the test statistic without the normality assumption, and obtain a necessary and sufficient condition for the chi-square limiting distribution to hold. Implications of the result are also discussed for the problem of dimension reduction. © 2003 Elsevier Science (USA). All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/S0047-259X(03)00056-3
dc.sourceScopus
dc.subjectCanonical correlation
dc.subjectChi-square test
dc.subjectDimension reduction
dc.subjectInverse regression
dc.subjectSIR models
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1016/S0047-259X(03)00056-3
dc.description.sourcetitleJournal of Multivariate Analysis
dc.description.volume88
dc.description.issue1
dc.description.page109-117
dc.description.codenJMVAA
dc.identifier.isiut000187785400007
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