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dc.contributor.advisorSmith, W. B.
dc.contributor.advisorRollins, J.
dc.creatorBohannon, Tommy R.
dc.date.accessioned2020-08-21T22:00:51Z
dc.date.available2020-08-21T22:00:51Z
dc.date.issued1976
dc.identifier.urihttps://hdl.handle.net/1969.1/DISSERTATIONS-614145
dc.descriptionVita.en
dc.description.abstractA procedure is proposed as a solution to the problem of constructing a classification rule based on samples which contain incomplete vectors. Simulation studies are made comparing this procedure to the standard procedure of ignoring these incomplete observations in the construction of the classification rule. The comparisons are made on the basis of the probability of misclassification.en
dc.format.extentix, 95 leaves ;en
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.rightsThis thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use.en
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectDiscriminant analysisen
dc.subjectMultivariate analysisen
dc.subjectMajor statisticsen
dc.subject.classification1976 Dissertation B676
dc.subject.lcshDiscriminant analysisen
dc.subject.lcshMultivariate analysisen
dc.titleDiscriminant analysis with missing dataen
dc.typeThesisen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameDoctor of Philosophyen
dc.type.genredissertationsen
dc.type.materialtexten
dc.format.digitalOriginreformatted digitalen
dc.publisher.digitalTexas A&M University. Libraries
dc.identifier.oclc2691378


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