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Effect of a missing observation on Hotelling's generalized T02
dc.contributor.authorKshirsagar, Anant M.en_US
dc.date.accessioned2006-04-07T20:47:53Z
dc.date.available2006-04-07T20:47:53Z
dc.date.issued1989-06en_US
dc.identifier.citationKshirsagar, Anant M. (1989/06)."Effect of a missing observation on Hotelling's generalized T02." Statistics &amp; Probability Letters 8(2): 163-166. <http://hdl.handle.net/2027.42/27904>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6V1D-45DHV07-19/2/cb8370203ed6c8e5f50155722fd959b7en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/27904
dc.description.abstractA generalization of the missing plot technique in univariate linear models to the multivariate case is given in this paper. The estimate of the missing observation vector produces the correct error matrix and the correct parameter estimates but the hypothesis matrix is biased. The adjustment required to the test, for achieving the desired level of significance, when the biased hypothesis matrix is used, is derived.en_US
dc.format.extent301927 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleEffect of a missing observation on Hotelling's generalized T02en_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelStatistics and Numeric Dataen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumBiostatistics Department, University of Michigan, Ann Arbor, MI 48109, USAen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/27904/1/0000324.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0167-7152(89)90010-2en_US
dc.identifier.sourceStatistics &amp; Probability Lettersen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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