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dc.contributor.advisorSmith, W. B.
dc.creatorRiggs, Mark William
dc.descriptionIncludes bibliographical references (leaves 62-65)en
dc.description.abstractA procedure is proposed as a solution to the problem of estimating canonical correlations using samples with missing observations. Simulation studies are made to compare this procedure to the common procedure of ignoring the incomplete observations in the estimation of the correlations. An application is made to the problem of constructing discriminant functions based on training data with incomplete observations. Also proposed are a measure of the possible reduction in variance of the estimates achieved by using the incomplete observations and a hypothesis test on the amount of information contained in the incomplete data.en
dc.format.extentvi, 69 leaves : illustrationsen
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.subject.classification1981 Dissertation R569
dc.subject.lcshMathematical statisticsen
dc.subject.lcshCorrelation (Statistics)en
dc.subject.lcshMultivariate analysisen
dc.subject.lcshCanonical correlation (Statistics)en
dc.subject.lcshDiscriminant analysisen
dc.titleCanonical correlation and discrimination with missing observationsen
dc.typeThesisen A&M Universityen of Philosophyen
dc.contributor.committeeMemberFeldman, Richard M.
dc.contributor.committeeMemberGates, Charles E.
dc.contributor.committeeMemberWehrly, Thomas E.
dc.format.digitalOriginreformatted digitalen
dc.publisher.digitalTexas A&M University. Libraries

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