Date of Award
Master of Science (MS)
Mathematics and Statistics
Ronald V. Canfield
Many procedures have been proposed for analyzing and describing multivariate dependence structure.
Partial correlation, multiple correlation, canonical correlation, principal component and factor analysis are used to analyze the dependence structures of a multinormal population.
For a partial correlation analysis it is necessary to decide which variables are to be correlated and which of the remaining variables must be held constant.
Multiple correlation demands that one variable be dependent upon some or all of the remaining variates.
For a canonical correlation, the variables must be collected into two or more sets. The factor analysis technique is for explaining the covariances of the variables and the principal component technique is for explaining the variance of the variables.
The principal component technique consists of an orthogonal transformation of the coordinate axes of a multivariate system to new orientations.
Kim, Chong S., "Canonical Analysis of Several Sets of Variables" (1973). All Graduate Plan B and other Reports. 1165.
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